Model save

README.md

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+---
+license: mit
+base_model: gpt2
+tags:
+- generated_from_trainer
+datasets:
+- bigbench
+metrics:
+- accuracy
+model-index:
+- name: bigbench_entailedpolarity-gpt2
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: bigbench
+      type: bigbench
+      config: entailed_polarity
+      split: train
+      args: entailed_polarity
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9166666666666666
+---
+
+<!-- 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. -->
+
+# bigbench_entailedpolarity-gpt2
+
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the bigbench dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0213
+- Accuracy: 0.9167
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 24   | 0.5201          | 0.875    |
+| No log        | 2.0   | 48   | 0.3512          | 0.875    |
+| No log        | 3.0   | 72   | 0.4245          | 0.8333   |
+| No log        | 4.0   | 96   | 0.3220          | 0.9167   |
+| No log        | 5.0   | 120  | 0.3962          | 0.875    |
+| No log        | 6.0   | 144  | 0.5551          | 0.875    |
+| No log        | 7.0   | 168  | 0.8597          | 0.875    |
+| No log        | 8.0   | 192  | 0.4610          | 0.9583   |
+| No log        | 9.0   | 216  | 0.9003          | 0.9167   |
+| No log        | 10.0  | 240  | 0.8778          | 0.9167   |
+| No log        | 11.0  | 264  | 0.9036          | 0.9167   |
+| No log        | 12.0  | 288  | 0.9188          | 0.9167   |
+| No log        | 13.0  | 312  | 1.0192          | 0.9167   |
+| No log        | 14.0  | 336  | 0.9984          | 0.9167   |
+| No log        | 15.0  | 360  | 0.9718          | 0.9167   |
+| No log        | 16.0  | 384  | 0.9882          | 0.9167   |
+| No log        | 17.0  | 408  | 1.0189          | 0.9167   |
+| No log        | 18.0  | 432  | 1.0210          | 0.9167   |
+| No log        | 19.0  | 456  | 1.0211          | 0.9167   |
+| No log        | 20.0  | 480  | 1.0213          | 0.9167   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 1.10.1+cu102
+- Datasets 2.15.0
+- Tokenizers 0.15.0

config.json

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+{
+  "_name_or_path": "gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2ForSequenceClassification"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "pad_token_id": 50256,
+  "problem_type": "single_label_classification",
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2",
+  "use_cache": true,
+  "vocab_size": 50257
+}

model.safetensors

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runs/Mar22_22-11-11_dsail2/events.out.tfevents.1711159873.dsail2.24990.0

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training_args.bin

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