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---
library_name: transformers
license: apache-2.0
base_model: distilgpt2
tags:
- generated_from_trainer
model-index:
- name: distilgpt2-finetuned
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. -->
# distilgpt2-finetuned
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6391
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.0748 | 0.0436 | 50 | 3.8923 |
| 3.8414 | 0.0871 | 100 | 3.8125 |
| 3.8957 | 0.1307 | 150 | 3.7769 |
| 3.8723 | 0.1743 | 200 | 3.7545 |
| 4.0205 | 0.2179 | 250 | 3.7336 |
| 3.7175 | 0.2614 | 300 | 3.7282 |
| 3.7778 | 0.3050 | 350 | 3.7111 |
| 3.7763 | 0.3486 | 400 | 3.6994 |
| 3.8142 | 0.3922 | 450 | 3.6945 |
| 3.7654 | 0.4357 | 500 | 3.6831 |
| 3.9636 | 0.4793 | 550 | 3.6773 |
| 3.703 | 0.5229 | 600 | 3.6692 |
| 3.6114 | 0.5664 | 650 | 3.6647 |
| 3.6269 | 0.6100 | 700 | 3.6591 |
| 3.693 | 0.6536 | 750 | 3.6564 |
| 3.7969 | 0.6972 | 800 | 3.6529 |
| 3.6011 | 0.7407 | 850 | 3.6491 |
| 3.4943 | 0.7843 | 900 | 3.6466 |
| 3.7543 | 0.8279 | 950 | 3.6440 |
| 3.861 | 0.8715 | 1000 | 3.6406 |
| 3.5354 | 0.9150 | 1050 | 3.6401 |
| 3.6661 | 0.9586 | 1100 | 3.6396 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
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