electra-copec-1 / README.md
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Training in progress epoch 1
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---
base_model: mrm8488/electricidad-base-discriminator
tags:
- generated_from_keras_callback
model-index:
- name: RafaelMayer/electra-copec-1
results: []
---
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# RafaelMayer/electra-copec-1
This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7863
- Validation Loss: 0.7271
- Train Accuracy: 0.1765
- Train Precision: [0.17647059 0. ]
- Train Precision W: 0.0311
- Train Recall: [1. 0.]
- Train Recall W: 0.1765
- Train F1: [0.3 0. ]
- Train F1 W: 0.0529
- 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 |
|:----------:|:---------------:|:--------------:|:-----------------------:|:-----------------:|:------------:|:--------------:|:---------:|:----------:|:-----:|
| 0.7863 | 0.7271 | 0.1765 | [0.17647059 0. ] | 0.0311 | [1. 0.] | 0.1765 | [0.3 0. ] | 0.0529 | 1 |
### Framework versions
- Transformers 4.32.1
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3