Training in progress, step 250, checkpoint

.gitattributes

@@ -38,3 +38,4 @@ checkpoint-50/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-100/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-150/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-200/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-250/tokenizer.json filter=lfs diff=lfs merge=lfs -text

checkpoint-250/README.md

@@ -0,0 +1,209 @@
+---
+base_model: google/medgemma-4b-it
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:google/medgemma-4b-it
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.16.0

checkpoint-250/adapter_config.json

@@ -0,0 +1,47 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "google/medgemma-4b-it",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "lm_head",
+    "embed_tokens"
+  ],
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "fc1",
+    "fc2",
+    "o_proj",
+    "gate_proj",
+    "up_proj",
+    "k_proj",
+    "down_proj",
+    "out_proj",
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-250/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:65dad601c602afe64cbc3e7cdea8b5468e88bb8eafe329270cfcd42b240cb186
+size 2839126480

checkpoint-250/added_tokens.json

@@ -0,0 +1,3 @@
+{
+  "<image_soft_token>": 262144
+}

checkpoint-250/chat_template.jinja

@@ -0,0 +1,47 @@
+{{ bos_token }}
+{%- if messages[0]['role'] == 'system' -%}
+    {%- if messages[0]['content'] is string -%}
+        {%- set first_user_prefix = messages[0]['content'] + '
+
+' -%}
+    {%- else -%}
+        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
+
+' -%}
+    {%- endif -%}
+    {%- set loop_messages = messages[1:] -%}
+{%- else -%}
+    {%- set first_user_prefix = "" -%}
+    {%- set loop_messages = messages -%}
+{%- endif -%}
+{%- for message in loop_messages -%}
+    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
+        {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
+    {%- endif -%}
+    {%- if (message['role'] == 'assistant') -%}
+        {%- set role = "model" -%}
+    {%- else -%}
+        {%- set role = message['role'] -%}
+    {%- endif -%}
+    {{ '<start_of_turn>' + role + '
+' + (first_user_prefix if loop.first else "") }}
+    {%- if message['content'] is string -%}
+        {{ message['content'] | trim }}
+    {%- elif message['content'] is iterable -%}
+        {%- for item in message['content'] -%}
+            {%- if item['type'] == 'image' -%}
+                {{ '<start_of_image>' }}
+            {%- elif item['type'] == 'text' -%}
+                {{ item['text'] | trim }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {{ raise_exception("Invalid content type") }}
+    {%- endif -%}
+    {{ '<end_of_turn>
+' }}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{'<start_of_turn>model
+'}}
+{%- endif -%}

checkpoint-250/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6742085ee357e4f252eba12c5c3fb54476fda396264a29ce393eabc60c9cfc42
+size 5678690152

checkpoint-250/preprocessor_config.json

@@ -0,0 +1,29 @@
+{
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_pan_and_scan": null,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "Gemma3ImageProcessor",
+  "image_seq_length": 256,
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "pan_and_scan_max_num_crops": null,
+  "pan_and_scan_min_crop_size": null,
+  "pan_and_scan_min_ratio_to_activate": null,
+  "processor_class": "Gemma3Processor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 896,
+    "width": 896
+  }
+}

checkpoint-250/processor_config.json

@@ -0,0 +1,4 @@
+{
+  "image_seq_length": 256,
+  "processor_class": "Gemma3Processor"
+}

checkpoint-250/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2cbf4c2e345635a9d5b1e040772b4c4c63ed5a9f1f46acc4b60011a5c86d3ef0
+size 14244

checkpoint-250/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a8154e662d7a91f508c9b0fb5f26a22e7c3848a42b473737a958e2a51bdde40
+size 1064

checkpoint-250/special_tokens_map.json

@@ -0,0 +1,33 @@
+{
+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
+    "content": "<eos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "image_token": "<image_soft_token>",
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-250/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1ebf1915455f8237564395182c49e3c685cfe3533b3d50ec6d49ce65ec43c32e
+size 33384723

checkpoint-250/tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1299c11d7cf632ef3b4e11937501358ada021bbdf7c47638d13c0ee982f2e79c
+size 4689074

checkpoint-250/trainer_state.json

@@ -0,0 +1,262 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.5202913631633714,
+  "eval_steps": 20,
+  "global_step": 250,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.04162330905306972,
+      "grad_norm": 20.466537475585938,
+      "learning_rate": 4.957081545064378e-05,
+      "loss": 8.8593,
+      "mean_token_accuracy": 0.6828776024281978,
+      "num_tokens": 161548.0,
+      "step": 20
+    },
+    {
+      "epoch": 0.04162330905306972,
+      "eval_loss": 1.1315333843231201,
+      "eval_mean_token_accuracy": 0.8237503719329834,
+      "eval_num_tokens": 161548.0,
+      "eval_runtime": 34.7122,
+      "eval_samples_per_second": 2.881,
+      "eval_steps_per_second": 0.72,
+      "step": 20
+    },
+    {
+      "epoch": 0.08324661810613944,
+      "grad_norm": 2.744436025619507,
+      "learning_rate": 4.742489270386266e-05,
+      "loss": 1.8553,
+      "mean_token_accuracy": 0.9392111219465733,
+      "num_tokens": 323168.0,
+      "step": 40
+    },
+    {
+      "epoch": 0.08324661810613944,
+      "eval_loss": 0.16864576935768127,
+      "eval_mean_token_accuracy": 0.9810383248329163,
+      "eval_num_tokens": 323168.0,
+      "eval_runtime": 34.3084,
+      "eval_samples_per_second": 2.915,
+      "eval_steps_per_second": 0.729,
+      "step": 40
+    },
+    {
+      "epoch": 0.12486992715920915,
+      "grad_norm": 1.6022675037384033,
+      "learning_rate": 4.527896995708155e-05,
+      "loss": 0.3903,
+      "mean_token_accuracy": 0.9888123281300067,
+      "num_tokens": 484780.0,
+      "step": 60
+    },
+    {
+      "epoch": 0.12486992715920915,
+      "eval_loss": 0.03530249744653702,
+      "eval_mean_token_accuracy": 0.9926152086257934,
+      "eval_num_tokens": 484780.0,
+      "eval_runtime": 34.7758,
+      "eval_samples_per_second": 2.876,
+      "eval_steps_per_second": 0.719,
+      "step": 60
+    },
+    {
+      "epoch": 0.16649323621227888,
+      "grad_norm": 1.2044650316238403,
+      "learning_rate": 4.313304721030043e-05,
+      "loss": 0.0664,
+      "mean_token_accuracy": 0.9934882044792175,
+      "num_tokens": 646431.0,
+      "step": 80
+    },
+    {
+      "epoch": 0.16649323621227888,
+      "eval_loss": 0.012011010199785233,
+      "eval_mean_token_accuracy": 0.9936227130889893,
+      "eval_num_tokens": 646431.0,
+      "eval_runtime": 34.3329,
+      "eval_samples_per_second": 2.913,
+      "eval_steps_per_second": 0.728,
+      "step": 80
+    },
+    {
+      "epoch": 0.2081165452653486,
+      "grad_norm": 0.4138229191303253,
+      "learning_rate": 4.098712446351932e-05,
+      "loss": 0.0513,
+      "mean_token_accuracy": 0.994041533768177,
+      "num_tokens": 808054.0,
+      "step": 100
+    },
+    {
+      "epoch": 0.2081165452653486,
+      "eval_loss": 0.011702906340360641,
+      "eval_mean_token_accuracy": 0.9942703366279602,
+      "eval_num_tokens": 808054.0,
+      "eval_runtime": 34.3225,
+      "eval_samples_per_second": 2.914,
+      "eval_steps_per_second": 0.728,
+      "step": 100
+    },
+    {
+      "epoch": 0.2497398543184183,
+      "grad_norm": 0.8489187955856323,
+      "learning_rate": 3.88412017167382e-05,
+      "loss": 0.0416,
+      "mean_token_accuracy": 0.9943524189293385,
+      "num_tokens": 969623.0,
+      "step": 120
+    },
+    {
+      "epoch": 0.2497398543184183,
+      "eval_loss": 0.010666043497622013,
+      "eval_mean_token_accuracy": 0.9943506979942321,
+      "eval_num_tokens": 969623.0,
+      "eval_runtime": 34.3761,
+      "eval_samples_per_second": 2.909,
+      "eval_steps_per_second": 0.727,
+      "step": 120
+    },
+    {
+      "epoch": 0.29136316337148804,
+      "grad_norm": 0.49626249074935913,
+      "learning_rate": 3.669527896995708e-05,
+      "loss": 0.0384,
+      "mean_token_accuracy": 0.9943184182047844,
+      "num_tokens": 1131222.0,
+      "step": 140
+    },
+    {
+      "epoch": 0.29136316337148804,
+      "eval_loss": 0.009807135909795761,
+      "eval_mean_token_accuracy": 0.9946736145019531,
+      "eval_num_tokens": 1131222.0,
+      "eval_runtime": 34.34,
+      "eval_samples_per_second": 2.912,
+      "eval_steps_per_second": 0.728,
+      "step": 140
+    },
+    {
+      "epoch": 0.33298647242455776,
+      "grad_norm": 0.5716305375099182,
+      "learning_rate": 3.454935622317597e-05,
+      "loss": 0.0384,
+      "mean_token_accuracy": 0.9946457795798779,
+      "num_tokens": 1292839.0,
+      "step": 160
+    },
+    {
+      "epoch": 0.33298647242455776,
+      "eval_loss": 0.009297176264226437,
+      "eval_mean_token_accuracy": 0.9946328043937683,
+      "eval_num_tokens": 1292839.0,
+      "eval_runtime": 34.557,
+      "eval_samples_per_second": 2.894,
+      "eval_steps_per_second": 0.723,
+      "step": 160
+    },
+    {
+      "epoch": 0.37460978147762747,
+      "grad_norm": 0.4264802932739258,
+      "learning_rate": 3.240343347639485e-05,
+      "loss": 0.0373,
+      "mean_token_accuracy": 0.9946053452789784,
+      "num_tokens": 1454417.0,
+      "step": 180
+    },
+    {
+      "epoch": 0.37460978147762747,
+      "eval_loss": 0.009250417351722717,
+      "eval_mean_token_accuracy": 0.9949553918838501,
+      "eval_num_tokens": 1454417.0,
+      "eval_runtime": 34.3425,
+      "eval_samples_per_second": 2.912,
+      "eval_steps_per_second": 0.728,
+      "step": 180
+    },
+    {
+      "epoch": 0.4162330905306972,
+      "grad_norm": 0.3315845727920532,
+      "learning_rate": 3.0257510729613737e-05,
+      "loss": 0.0326,
+      "mean_token_accuracy": 0.9949214711785317,
+      "num_tokens": 1615982.0,
+      "step": 200
+    },
+    {
+      "epoch": 0.4162330905306972,
+      "eval_loss": 0.00862209778279066,
+      "eval_mean_token_accuracy": 0.994794466495514,
+      "eval_num_tokens": 1615982.0,
+      "eval_runtime": 34.317,
+      "eval_samples_per_second": 2.914,
+      "eval_steps_per_second": 0.729,
+      "step": 200
+    },
+    {
+      "epoch": 0.4578563995837669,
+      "grad_norm": 0.3415542542934418,
+      "learning_rate": 2.811158798283262e-05,
+      "loss": 0.0328,
+      "mean_token_accuracy": 0.9948225237429142,
+      "num_tokens": 1777586.0,
+      "step": 220
+    },
+    {
+      "epoch": 0.4578563995837669,
+      "eval_loss": 0.008552273735404015,
+      "eval_mean_token_accuracy": 0.9952386736869812,
+      "eval_num_tokens": 1777586.0,
+      "eval_runtime": 34.357,
+      "eval_samples_per_second": 2.911,
+      "eval_steps_per_second": 0.728,
+      "step": 220
+    },
+    {
+      "epoch": 0.4994797086368366,
+      "grad_norm": 0.5801106691360474,
+      "learning_rate": 2.59656652360515e-05,
+      "loss": 0.0317,
+      "mean_token_accuracy": 0.9949369013309479,
+      "num_tokens": 1939204.0,
+      "step": 240
+    },
+    {
+      "epoch": 0.4994797086368366,
+      "eval_loss": 0.008411003276705742,
+      "eval_mean_token_accuracy": 0.9951176619529725,
+      "eval_num_tokens": 1939204.0,
+      "eval_runtime": 34.3383,
+      "eval_samples_per_second": 2.912,
+      "eval_steps_per_second": 0.728,
+      "step": 240
+    }
+  ],
+  "logging_steps": 20,
+  "max_steps": 481,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 1,
+  "save_steps": 50,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 5.274874606081766e+16,
+  "train_batch_size": 4,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-250/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dd8015c9bbe5c0dbff1905684d15785ccb3cb07ead997cd50301f35dcf48b143
+size 5880