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base_model: distilbert/distilroberta-base
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: my_model
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. -->
# my_model
This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7996
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 45
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 199 | 1.7128 |
| No log | 2.0 | 398 | 1.4856 |
| 1.8719 | 3.0 | 597 | 1.3661 |
| 1.8719 | 4.0 | 796 | 1.2638 |
| 1.8719 | 5.0 | 995 | 1.1847 |
| 1.3663 | 6.0 | 1194 | 1.1849 |
| 1.3663 | 7.0 | 1393 | 1.1757 |
| 1.2108 | 8.0 | 1592 | 1.1026 |
| 1.2108 | 9.0 | 1791 | 1.0826 |
| 1.2108 | 10.0 | 1990 | 1.0609 |
| 1.1079 | 11.0 | 2189 | 1.0221 |
| 1.1079 | 12.0 | 2388 | 1.0199 |
| 1.0428 | 13.0 | 2587 | 0.9990 |
| 1.0428 | 14.0 | 2786 | 1.0083 |
| 1.0428 | 15.0 | 2985 | 0.9905 |
| 0.9911 | 16.0 | 3184 | 0.9492 |
| 0.9911 | 17.0 | 3383 | 0.9526 |
| 0.9391 | 18.0 | 3582 | 0.9219 |
| 0.9391 | 19.0 | 3781 | 0.9228 |
| 0.9391 | 20.0 | 3980 | 0.9183 |
| 0.9078 | 21.0 | 4179 | 0.9276 |
| 0.9078 | 22.0 | 4378 | 0.8874 |
| 0.8727 | 23.0 | 4577 | 0.8856 |
| 0.8727 | 24.0 | 4776 | 0.8899 |
| 0.8727 | 25.0 | 4975 | 0.8836 |
| 0.8513 | 26.0 | 5174 | 0.8790 |
| 0.8513 | 27.0 | 5373 | 0.8835 |
| 0.8145 | 28.0 | 5572 | 0.8583 |
| 0.8145 | 29.0 | 5771 | 0.8498 |
| 0.8145 | 30.0 | 5970 | 0.8530 |
| 0.8085 | 31.0 | 6169 | 0.8409 |
| 0.8085 | 32.0 | 6368 | 0.8196 |
| 0.7783 | 33.0 | 6567 | 0.8311 |
| 0.7783 | 34.0 | 6766 | 0.8301 |
| 0.7783 | 35.0 | 6965 | 0.8370 |
| 0.7639 | 36.0 | 7164 | 0.8321 |
| 0.7639 | 37.0 | 7363 | 0.8226 |
| 0.757 | 38.0 | 7562 | 0.8361 |
| 0.757 | 39.0 | 7761 | 0.8236 |
| 0.757 | 40.0 | 7960 | 0.8255 |
| 0.7483 | 41.0 | 8159 | 0.8305 |
| 0.7483 | 42.0 | 8358 | 0.8057 |
| 0.7449 | 43.0 | 8557 | 0.8251 |
| 0.7449 | 44.0 | 8756 | 0.8014 |
| 0.7449 | 45.0 | 8955 | 0.7996 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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