result_llm / README.md
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---
license: apache-2.0
base_model: distilbert/distilgpt2
tags:
- generated_from_trainer
model-index:
- name: result_llm
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. -->
# result_llm
This model is a fine-tuned version of [distilbert/distilgpt2](https://huggingface.co/distilbert/distilgpt2) on an unknown 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 8.289 | 0.0554 | 500 | nan |
| 6.8357 | 0.1109 | 1000 | nan |
| 6.7413 | 0.1663 | 1500 | nan |
| 6.6101 | 0.2218 | 2000 | nan |
| 6.6348 | 0.2772 | 2500 | nan |
| 6.6871 | 0.3326 | 3000 | nan |
| 6.602 | 0.3881 | 3500 | nan |
| 6.6078 | 0.4435 | 4000 | nan |
| 6.5465 | 0.4989 | 4500 | nan |
| 6.5643 | 0.5544 | 5000 | nan |
| 6.5696 | 0.6098 | 5500 | nan |
| 6.5294 | 0.6653 | 6000 | nan |
| 6.5638 | 0.7207 | 6500 | nan |
| 6.4361 | 0.7761 | 7000 | nan |
| 6.4547 | 0.8316 | 7500 | nan |
| 6.5327 | 0.8870 | 8000 | nan |
| 6.3524 | 0.9425 | 8500 | nan |
| 6.4341 | 0.9979 | 9000 | nan |
| 6.3677 | 1.0533 | 9500 | nan |
| 6.199 | 1.1088 | 10000 | nan |
| 6.3033 | 1.1642 | 10500 | nan |
| 6.2976 | 1.2196 | 11000 | nan |
| 6.2322 | 1.2751 | 11500 | nan |
| 6.2222 | 1.3305 | 12000 | nan |
| 6.2119 | 1.3860 | 12500 | nan |
| 6.2336 | 1.4414 | 13000 | nan |
| 6.349 | 1.4968 | 13500 | nan |
| 6.311 | 1.5523 | 14000 | nan |
| 6.2247 | 1.6077 | 14500 | nan |
| 6.2851 | 1.6632 | 15000 | nan |
| 6.35 | 1.7186 | 15500 | nan |
| 6.2996 | 1.7740 | 16000 | nan |
| 6.3229 | 1.8295 | 16500 | nan |
| 6.3609 | 1.8849 | 17000 | nan |
| 6.3063 | 1.9403 | 17500 | nan |
| 6.2759 | 1.9958 | 18000 | nan |
| 6.2499 | 2.0512 | 18500 | nan |
| 6.1473 | 2.1067 | 19000 | nan |
| 6.2088 | 2.1621 | 19500 | nan |
| 6.2482 | 2.2175 | 20000 | nan |
| 6.2123 | 2.2730 | 20500 | nan |
| 6.2298 | 2.3284 | 21000 | nan |
| 6.2666 | 2.3839 | 21500 | nan |
| 6.21 | 2.4393 | 22000 | nan |
| 6.2396 | 2.4947 | 22500 | nan |
| 6.2626 | 2.5502 | 23000 | nan |
| 6.1824 | 2.6056 | 23500 | nan |
| 6.3142 | 2.6610 | 24000 | nan |
| 6.2816 | 2.7165 | 24500 | nan |
| 6.2371 | 2.7719 | 25000 | nan |
| 6.3075 | 2.8274 | 25500 | nan |
| 6.2306 | 2.8828 | 26000 | nan |
| 6.2919 | 2.9382 | 26500 | nan |
| 6.2668 | 2.9937 | 27000 | nan |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Tokenizers 0.19.1