File size: 2,986 Bytes
0cc13ab |
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 78 79 80 81 82 83 84 85 |
---
library_name: transformers
license: apache-2.0
base_model: EuroBERT/EuroBERT-210m
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: eurobert210m_Eau_v2
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. -->
# eurobert210m_Eau_v2
This model is a fine-tuned version of [EuroBERT/EuroBERT-210m](https://huggingface.co/EuroBERT/EuroBERT-210m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0680
- Accuracy: 0.9584
- F1: 0.9595
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.4372 | 1.0 | 67 | 0.9689 | 0.6322 | 0.5664 |
| 0.8205 | 2.0 | 134 | 0.6235 | 0.8213 | 0.8222 |
| 0.4899 | 3.0 | 201 | 0.4782 | 0.8326 | 0.8367 |
| 0.3598 | 4.0 | 268 | 0.2252 | 0.9196 | 0.9200 |
| 0.2854 | 5.0 | 335 | 0.2137 | 0.9258 | 0.9265 |
| 0.2054 | 6.0 | 402 | 0.1284 | 0.9452 | 0.9443 |
| 0.1735 | 7.0 | 469 | 0.1984 | 0.9296 | 0.9303 |
| 0.1763 | 8.0 | 536 | 0.1177 | 0.9409 | 0.9379 |
| 0.1601 | 9.0 | 603 | 0.1133 | 0.9485 | 0.9462 |
| 0.1206 | 10.0 | 670 | 0.1219 | 0.9461 | 0.9448 |
| 0.1269 | 11.0 | 737 | 0.0756 | 0.9565 | 0.9575 |
| 0.1238 | 12.0 | 804 | 0.1025 | 0.9522 | 0.9539 |
| 0.0969 | 13.0 | 871 | 0.0823 | 0.9570 | 0.9580 |
| 0.1046 | 14.0 | 938 | 0.0802 | 0.9527 | 0.9513 |
| 0.1101 | 15.0 | 1005 | 0.0797 | 0.9546 | 0.9539 |
| 0.0864 | 16.0 | 1072 | 0.0853 | 0.9565 | 0.9550 |
| 0.1002 | 17.0 | 1139 | 0.0696 | 0.9579 | 0.9582 |
| 0.0794 | 18.0 | 1206 | 0.0774 | 0.9579 | 0.9588 |
| 0.0849 | 19.0 | 1273 | 0.0719 | 0.9546 | 0.9529 |
| 0.0867 | 20.0 | 1340 | 0.0723 | 0.9589 | 0.9575 |
| 0.0952 | 21.0 | 1407 | 0.0680 | 0.9584 | 0.9595 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
|