File size: 2,473 Bytes
d58d27a |
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 |
---
license: apache-2.0
base_model: PlanTL-GOB-ES/roberta-base-bne
tags:
- generated_from_keras_callback
model-index:
- name: RafaelMayer/roberta-copec-1
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# RafaelMayer/roberta-copec-1
This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.6572
- Validation Loss: 0.6316
- Train Accuracy: 0.8235
- Train Precision: [0. 0.82352941]
- Train Precision W: 0.6782
- Train Recall: [0. 1.]
- Train Recall W: 0.8235
- Train F1: [0. 0.90322581]
- Train F1 W: 0.7438
- Epoch: 1
## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 35, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 5, 'power': 1.0, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Train Precision | Train Precision W | Train Recall | Train Recall W | Train F1 | Train F1 W | Epoch |
|:----------:|:---------------:|:--------------:|:-----------------------:|:-----------------:|:------------:|:--------------:|:-----------------------:|:----------:|:-----:|
| 0.6572 | 0.6316 | 0.8235 | [0. 0.82352941] | 0.6782 | [0. 1.] | 0.8235 | [0. 0.90322581] | 0.7438 | 1 |
### Framework versions
- Transformers 4.32.1
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
|