File size: 2,270 Bytes
5c00869 35daf7d 5c00869 35daf7d 5c00869 8f7c618 5c00869 8f7c618 5c00869 8f7c618 5c00869 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
license: mit
tags:
- generated_from_trainer
model-index:
- name: fr-camembert-base-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. -->
# fr-camembert-base-finetuned
This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3301
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.2487 | 1.0 | 124 | 2.8169 |
| 2.6851 | 2.0 | 248 | 2.6374 |
| 2.6175 | 3.0 | 372 | 2.6431 |
| 2.5366 | 4.0 | 496 | 2.4475 |
| 2.4529 | 5.0 | 620 | 2.4647 |
| 2.4002 | 6.0 | 744 | 2.4846 |
| 2.3914 | 7.0 | 868 | 2.4187 |
| 2.3439 | 8.0 | 992 | 2.4819 |
| 2.2797 | 9.0 | 1116 | 2.3769 |
| 2.3065 | 10.0 | 1240 | 2.4536 |
| 2.2499 | 11.0 | 1364 | 2.4079 |
| 2.2254 | 12.0 | 1488 | 2.3755 |
| 2.218 | 13.0 | 1612 | 2.3189 |
| 2.2059 | 14.0 | 1736 | 2.3628 |
| 2.158 | 15.0 | 1860 | 2.4482 |
| 2.1871 | 16.0 | 1984 | 2.3020 |
| 2.154 | 17.0 | 2108 | 2.3485 |
| 2.1906 | 18.0 | 2232 | 2.4602 |
| 2.1853 | 19.0 | 2356 | 2.2482 |
| 2.1334 | 20.0 | 2480 | 2.3699 |
### Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
|