File size: 2,405 Bytes
c008ba0 |
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 |
---
base_model: dccuchile/bert-base-spanish-wwm-uncased
tags:
- generated_from_trainer
model-index:
- name: bert_adaptation_resenas_de_vinos_2023_11_25_15_31
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. -->
# bert_adaptation_resenas_de_vinos_2023_11_25_15_31
This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-uncased](https://huggingface.co./dccuchile/bert-base-spanish-wwm-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6461
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 3.9807 | 1.0 | 250 | 3.0434 |
| 3.0811 | 2.0 | 500 | 3.1461 |
| 2.7704 | 3.0 | 750 | 2.9649 |
| 2.6821 | 4.0 | 1000 | 2.8179 |
| 2.556 | 5.0 | 1250 | 2.6522 |
| 2.3324 | 6.0 | 1500 | 2.7123 |
| 2.3137 | 7.0 | 1750 | 2.5994 |
| 2.2926 | 8.0 | 2000 | 2.6741 |
| 2.1216 | 9.0 | 2250 | 2.6469 |
| 2.0317 | 10.0 | 2500 | 2.6205 |
| 2.0053 | 11.0 | 2750 | 2.4237 |
| 2.0453 | 12.0 | 3000 | 2.5970 |
| 1.9702 | 13.0 | 3250 | 2.4548 |
| 1.9147 | 14.0 | 3500 | 2.4731 |
| 1.9143 | 15.0 | 3750 | 2.4431 |
| 1.7803 | 16.0 | 4000 | 2.4247 |
| 1.7726 | 17.0 | 4250 | 2.5558 |
| 1.7448 | 18.0 | 4500 | 2.5092 |
| 1.7008 | 19.0 | 4750 | 2.4883 |
| 1.769 | 20.0 | 5000 | 2.4471 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|