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--- |
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license: mit |
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base_model: gpt2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: 4_bar_lmd_clean_custom_test3 |
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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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# 4_bar_lmd_clean_custom_test3 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 4.4912 |
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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: 0.005 |
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- train_batch_size: 48 |
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- eval_batch_size: 32 |
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- seed: 1 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 96 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.01 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 6.8709 | 1.82 | 10 | 5.7363 | |
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| 5.6849 | 3.64 | 20 | 5.4321 | |
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| 5.4501 | 5.45 | 30 | 5.3610 | |
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| 5.359 | 7.27 | 40 | 5.2833 | |
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| 5.278 | 9.09 | 50 | 5.1274 | |
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| 5.1335 | 10.91 | 60 | 5.0075 | |
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| 5.0548 | 12.73 | 70 | 4.9488 | |
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| 4.958 | 14.55 | 80 | 4.8213 | |
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| 4.8511 | 16.36 | 90 | 4.7643 | |
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| 4.8158 | 18.18 | 100 | 4.7202 | |
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| 4.7548 | 20.0 | 110 | 4.6591 | |
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| 4.7269 | 21.82 | 120 | 4.6380 | |
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| 4.6823 | 23.64 | 130 | 4.6200 | |
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| 4.6757 | 25.45 | 140 | 4.6081 | |
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| 4.629 | 27.27 | 150 | 4.6285 | |
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| 4.6398 | 29.09 | 160 | 4.6024 | |
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| 4.6111 | 30.91 | 170 | 4.6235 | |
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| 4.6028 | 32.73 | 180 | 4.5945 | |
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| 4.577 | 34.55 | 190 | 4.5932 | |
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| 4.5812 | 36.36 | 200 | 4.5689 | |
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| 4.5583 | 38.18 | 210 | 4.5713 | |
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| 4.5567 | 40.0 | 220 | 4.5731 | |
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| 4.55 | 41.82 | 230 | 4.5619 | |
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| 4.5338 | 43.64 | 240 | 4.5656 | |
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| 4.5245 | 45.45 | 250 | 4.5494 | |
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| 4.5143 | 47.27 | 260 | 4.5578 | |
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| 4.5339 | 49.09 | 270 | 4.5489 | |
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| 4.4948 | 50.91 | 280 | 4.5746 | |
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| 4.5 | 52.73 | 290 | 4.5407 | |
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| 4.4755 | 54.55 | 300 | 4.5448 | |
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| 4.4736 | 56.36 | 310 | 4.5311 | |
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| 4.4584 | 58.18 | 320 | 4.5279 | |
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| 4.465 | 60.0 | 330 | 4.5339 | |
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| 4.4511 | 61.82 | 340 | 4.5326 | |
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| 4.4408 | 63.64 | 350 | 4.5163 | |
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| 4.4314 | 65.45 | 360 | 4.5193 | |
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| 4.417 | 67.27 | 370 | 4.5161 | |
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| 4.424 | 69.09 | 380 | 4.5027 | |
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| 4.4147 | 70.91 | 390 | 4.5044 | |
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| 4.3938 | 72.73 | 400 | 4.5012 | |
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| 4.4001 | 74.55 | 410 | 4.5037 | |
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| 4.3821 | 76.36 | 420 | 4.5006 | |
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| 4.383 | 78.18 | 430 | 4.4981 | |
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| 4.3893 | 80.0 | 440 | 4.4942 | |
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| 4.3684 | 81.82 | 450 | 4.4927 | |
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| 4.3788 | 83.64 | 460 | 4.4933 | |
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| 4.3836 | 85.45 | 470 | 4.4929 | |
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| 4.3766 | 87.27 | 480 | 4.4917 | |
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| 4.3871 | 89.09 | 490 | 4.4912 | |
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| 4.3725 | 90.91 | 500 | 4.4912 | |
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### Framework versions |
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- Transformers 4.36.0 |
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- Pytorch 2.1.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.1 |
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