finetuned vicuna with medusa and snapkv

README.md

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+---
+library_name: transformers
+license: llama2
+base_model: lmsys/vicuna-7b-v1.5
+tags:
+- generated_from_trainer
+model-index:
+- name: vicuna_7b_stage1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+# vicuna_7b_stage1
+
+This model is a fine-tuned version of [lmsys/vicuna-7b-v1.5](https://huggingface.co/lmsys/vicuna-7b-v1.5) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0005
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 40
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 3.0038        | 0.0410 | 40   | nan             |
+| 2.881         | 0.0821 | 80   | nan             |
+| 2.7344        | 0.1231 | 120  | nan             |
+| 2.7523        | 0.1641 | 160  | nan             |
+| 2.8974        | 0.2051 | 200  | nan             |
+| 2.8822        | 0.2462 | 240  | nan             |
+| 2.8679        | 0.2872 | 280  | nan             |
+| 2.8764        | 0.3282 | 320  | nan             |
+| 2.7328        | 0.3692 | 360  | nan             |
+| 2.6559        | 0.4103 | 400  | nan             |
+| 2.9797        | 0.4513 | 440  | nan             |
+| 2.6416        | 0.4923 | 480  | nan             |
+| 2.5732        | 0.5333 | 520  | nan             |
+| 2.5785        | 0.5744 | 560  | nan             |
+| 2.6892        | 0.6154 | 600  | nan             |
+| 2.5908        | 0.6564 | 640  | nan             |
+| 2.5158        | 0.6974 | 680  | nan             |
+| 2.43          | 0.7385 | 720  | nan             |
+| 2.4511        | 0.7795 | 760  | nan             |
+| 2.3835        | 0.8205 | 800  | nan             |
+| 2.1151        | 0.8615 | 840  | nan             |
+| 2.4363        | 0.9026 | 880  | nan             |
+| 2.3235        | 0.9436 | 920  | nan             |
+| 2.2581        | 0.9846 | 960  | nan             |
+| 2.1462        | 1.0256 | 1000 | nan             |
+| 2.163         | 1.0667 | 1040 | nan             |
+| 2.2433        | 1.1077 | 1080 | nan             |
+| 2.0609        | 1.1487 | 1120 | nan             |
+| 1.9598        | 1.1897 | 1160 | nan             |
+| 2.1146        | 1.2308 | 1200 | nan             |
+| 2.0555        | 1.2718 | 1240 | nan             |
+| 1.8906        | 1.3128 | 1280 | nan             |
+| 1.8369        | 1.3538 | 1320 | nan             |
+| 1.9503        | 1.3949 | 1360 | nan             |
+| 1.8217        | 1.4359 | 1400 | nan             |
+| 1.9437        | 1.4769 | 1440 | nan             |
+| 1.7392        | 1.5179 | 1480 | nan             |
+| 1.7494        | 1.5590 | 1520 | nan             |
+| 1.7624        | 1.6    | 1560 | nan             |
+| 1.7191        | 1.6410 | 1600 | nan             |
+| 1.8216        | 1.6821 | 1640 | nan             |
+| 1.7724        | 1.7231 | 1680 | nan             |
+| 1.78          | 1.7641 | 1720 | nan             |
+| 1.5865        | 1.8051 | 1760 | nan             |
+| 1.7514        | 1.8462 | 1800 | nan             |
+| 1.7128        | 1.8872 | 1840 | nan             |
+| 1.8041        | 1.9282 | 1880 | nan             |
+| 1.6393        | 1.9692 | 1920 | nan             |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.6.0.dev20241122+rocm6.2
+- Datasets 2.14.7
+- Tokenizers 0.20.3

checkpoint-1950/config.json

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+{
+  "_name_or_path": "lmsys/vicuna-7b-v1.5",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
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+  "bos_token_id": 1,
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+  "head_dim": 128,
+  "hidden_act": "silu",
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+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "kernel_size": 5,
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+  "max_position_embeddings": 4096,
+  "medusa_num_heads": 5,
+  "medusa_num_layers": 1,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pad_token_id": 0,
+  "pooling": "avgpool",
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
+  "use_cache": false,
+  "vocab_size": 32000,
+  "window_size": 32
+}

checkpoint-1950/generation_config.json

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+  "max_length": 4096,
+  "pad_token_id": 0,
+  "temperature": null,
+  "top_p": null,
+  "transformers_version": "4.45.2"
+}

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