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---
license: mit
tags:
- generated_from_keras_callback
model-index:
- name: italian-literature-model-mini
results: []
widget:
- text: "un azzurro metallico"
- text: "il sole alto"
- text: "una barca a vela"
- text: "mare calmo"
- text: "all'improvviso"
- text: "una visione inaspettata"
---
<!-- 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. -->
# italian-literature-model-mini
This model is a fine-tuned version of [gpt2](https://huggingface.co./gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 5.7067
- Validation Loss: 5.6842
- Epoch: 2
## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 15686, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
### Training results
| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 5.7065 | 5.6842 | 0 |
| 5.7065 | 5.6842 | 1 |
| 5.7067 | 5.6842 | 2 |
### Framework versions
- Transformers 4.26.0
- TensorFlow 2.9.2
- Datasets 2.9.0
- Tokenizers 0.13.2
|