mhr2004/answerdotai-ModernBERT-base-anion-neg-bal-1e-06-256

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: answerdotai/ModernBERT-base
+tags:
+- generated_from_trainer
+model-index:
+- name: answerdotai-ModernBERT-base-anion-neg-bal-1e-06-256
+  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. -->
+
+# answerdotai-ModernBERT-base-anion-neg-bal-1e-06-256
+
+This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3196
+
+## 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: 1e-06
+- train_batch_size: 256
+- eval_batch_size: 256
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.6865        | 1.0   | 358  | 0.5785          |
+| 0.5191        | 2.0   | 716  | 0.4656          |
+| 0.435         | 3.0   | 1074 | 0.4231          |
+| 0.3931        | 4.0   | 1432 | 0.3961          |
+| 0.3758        | 5.0   | 1790 | 0.3774          |
+| 0.3458        | 6.0   | 2148 | 0.3627          |
+| 0.3247        | 7.0   | 2506 | 0.3526          |
+| 0.3032        | 8.0   | 2864 | 0.3431          |
+| 0.2864        | 9.0   | 3222 | 0.3359          |
+| 0.2804        | 10.0  | 3580 | 0.3331          |
+| 0.2644        | 11.0  | 3938 | 0.3240          |
+| 0.254         | 12.0  | 4296 | 0.3206          |
+| 0.2406        | 13.0  | 4654 | 0.3191          |
+| 0.2324        | 14.0  | 5012 | 0.3188          |
+| 0.2242        | 15.0  | 5370 | 0.3189          |
+| 0.2139        | 16.0  | 5728 | 0.3159          |
+| 0.2087        | 17.0  | 6086 | 0.3166          |
+| 0.2019        | 18.0  | 6444 | 0.3151          |
+| 0.1984        | 19.0  | 6802 | 0.3173          |
+| 0.1887        | 20.0  | 7160 | 0.3203          |
+| 0.1814        | 21.0  | 7518 | 0.3196          |
+
+
+### Framework versions
+
+- Transformers 4.49.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.1

config.json

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+{
+  "_name_or_path": "answerdotai/ModernBERT-base",
+  "architectures": [
+    "ModernBertForSequenceClassification"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 50281,
+  "classifier_activation": "gelu",
+  "classifier_bias": false,
+  "classifier_dropout": 0.0,
+  "classifier_pooling": "mean",
+  "cls_token_id": 50281,
+  "decoder_bias": true,
+  "deterministic_flash_attn": false,
+  "embedding_dropout": 0.0,
+  "eos_token_id": 50282,
+  "global_attn_every_n_layers": 3,
+  "global_rope_theta": 160000.0,
+  "gradient_checkpointing": false,
+  "hidden_activation": "gelu",
+  "hidden_size": 768,
+  "initializer_cutoff_factor": 2.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 1152,
+  "layer_norm_eps": 1e-05,
+  "local_attention": 128,
+  "local_rope_theta": 10000.0,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "mlp_dropout": 0.0,
+  "model_type": "modernbert",
+  "norm_bias": false,
+  "norm_eps": 1e-05,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 22,
+  "pad_token_id": 50283,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "reference_compile": true,
+  "repad_logits_with_grad": false,
+  "sep_token_id": 50282,
+  "sparse_pred_ignore_index": -100,
+  "sparse_prediction": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.49.0",
+  "vocab_size": 50368
+}

model.safetensors

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training_args.bin

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