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bertin-roberta-base-spanish-finetuned-recores3
versae/bertin-roberta-base-spanish-finetuned-recores3
bertin-roberta-base-spanish-finetuned-recores3 is a multiple choice model from versae. Use it for the multiple choice task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as cc-by-4.0.
should probably proofread and complete it, then remove this comment. --
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Model card
From the Hugging Face model README
<!-- 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. -->
bertin-roberta-base-spanish-finetuned-recores3
This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 6.0975
- Accuracy: 0.3884
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.6095 | 1.0 | 524 | 1.6094 | 0.2342 |
| 1.607 | 2.0 | 1048 | 1.5612 | 0.3058 |
| 1.4059 | 3.0 | 1572 | 1.6292 | 0.3361 |
| 0.7047 | 4.0 | 2096 | 2.5111 | 0.4132 |
| 0.2671 | 5.0 | 2620 | 3.2399 | 0.3499 |
| 0.1065 | 6.0 | 3144 | 5.1217 | 0.3444 |
| 0.0397 | 7.0 | 3668 | 4.3270 | 0.3691 |
| 0.0162 | 8.0 | 4192 | 5.1796 | 0.3719 |
| 0.0096 | 9.0 | 4716 | 5.2161 | 0.3994 |
| 0.0118 | 10.0 | 5240 | 4.9225 | 0.3719 |
| 0.0015 | 11.0 | 5764 | 5.0544 | 0.3829 |
| 0.0091 | 12.0 | 6288 | 5.7731 | 0.3884 |
| 0.0052 | 13.0 | 6812 | 4.1606 | 0.3939 |
| 0.0138 | 14.0 | 7336 | 6.2725 | 0.3857 |
| 0.0027 | 15.0 | 7860 | 6.2274 | 0.3857 |
| 0.0003 | 16.0 | 8384 | 6.0935 | 0.4022 |
| 0.0002 | 17.0 | 8908 | 5.7650 | 0.3994 |
| 0.0 | 18.0 | 9432 | 6.3595 | 0.4215 |
| 0.0 | 19.0 | 9956 | 5.8934 | 0.3747 |
| 0.0001 | 20.0 | 10480 | 6.0571 | 0.3884 |
| 0.0 | 21.0 | 11004 | 6.0718 | 0.3884 |
| 0.0 | 22.0 | 11528 | 6.0844 | 0.3884 |
| 0.0 | 23.0 | 12052 | 6.0930 | 0.3884 |
| 0.0 | 24.0 | 12576 | 6.0966 | 0.3884 |
| 0.0 | 25.0 | 13100 | 6.0975 | 0.3884 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Task
- multiple choice
- Library
- transformers
- Type
- roberta
- License
- cc-by-4.0
- Created
- May 23, 2022
- Updated
- Feb 16, 2025