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--- |
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library_name: transformers |
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license: mit |
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base_model: microsoft/DialoGPT-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: dialochess-v4 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# dialochess-v4 |
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This model is a fine-tuned version of [microsoft/DialoGPT-small](https://huggingface.co/microsoft/DialoGPT-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8124 |
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- Accuracy: 0.0004 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- num_epochs: 6 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 1.3141 | 0.1616 | 200 | 1.1921 | 0.0002 | |
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| 1.194 | 0.3231 | 400 | 1.0974 | 0.0003 | |
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| 1.118 | 0.4847 | 600 | 1.0425 | 0.0 | |
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| 1.0767 | 0.6462 | 800 | 1.0071 | 0.0 | |
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| 1.0414 | 0.8078 | 1000 | 0.9825 | 0.0005 | |
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| 1.0158 | 0.9693 | 1200 | 0.9601 | 0.0002 | |
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| 1.0035 | 1.1309 | 1400 | 0.9427 | 0.0001 | |
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| 0.9715 | 1.2924 | 1600 | 0.9300 | 0.0002 | |
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| 0.9745 | 1.4540 | 1800 | 0.9193 | 0.0002 | |
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| 0.9447 | 1.6155 | 2000 | 0.9063 | 0.0002 | |
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| 0.9573 | 1.7771 | 2200 | 0.8980 | 0.0005 | |
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| 0.9386 | 1.9386 | 2400 | 0.8893 | 0.0003 | |
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| 0.9204 | 2.1002 | 2600 | 0.8786 | 0.0003 | |
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| 0.9128 | 2.2617 | 2800 | 0.8732 | 0.0003 | |
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| 0.9079 | 2.4233 | 3000 | 0.8670 | 0.0002 | |
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| 0.9073 | 2.5848 | 3200 | 0.8603 | 0.0002 | |
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| 0.8938 | 2.7464 | 3400 | 0.8532 | 0.0004 | |
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| 0.8899 | 2.9079 | 3600 | 0.8501 | 0.0002 | |
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| 0.8834 | 3.0695 | 3800 | 0.8426 | 0.0002 | |
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| 0.8693 | 3.2310 | 4000 | 0.8416 | 0.0003 | |
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| 0.8808 | 3.3926 | 4200 | 0.8335 | 0.0002 | |
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| 0.872 | 3.5541 | 4400 | 0.8297 | 0.0003 | |
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| 0.8689 | 3.7157 | 4600 | 0.8296 | 0.0003 | |
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| 0.8607 | 3.8772 | 4800 | 0.8237 | 0.0002 | |
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| 0.8516 | 4.0388 | 5000 | 0.8246 | 0.0004 | |
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| 0.8652 | 4.2003 | 5200 | 0.8210 | 0.0004 | |
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| 0.8522 | 4.3619 | 5400 | 0.8192 | 0.0003 | |
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| 0.8466 | 4.5234 | 5600 | 0.8181 | 0.0002 | |
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| 0.8525 | 4.6850 | 5800 | 0.8163 | 0.0004 | |
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| 0.8485 | 4.8465 | 6000 | 0.8163 | 0.0004 | |
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| 0.8444 | 5.0081 | 6200 | 0.8144 | 0.0003 | |
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| 0.8512 | 5.1696 | 6400 | 0.8141 | 0.0004 | |
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| 0.8405 | 5.3312 | 6600 | 0.8135 | 0.0004 | |
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| 0.8337 | 5.4927 | 6800 | 0.8124 | 0.0004 | |
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| 0.8601 | 5.6543 | 7000 | 0.8125 | 0.0004 | |
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| 0.8506 | 5.8158 | 7200 | 0.8124 | 0.0004 | |
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| 0.8562 | 5.9774 | 7400 | 0.8124 | 0.0004 | |
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### Framework versions |
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- Transformers 4.57.2 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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