Instructions to use vladjr/bart-base-teste2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vladjr/bart-base-teste2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vladjr/bart-base-teste2") model = AutoModelForSeq2SeqLM.from_pretrained("vladjr/bart-base-teste2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from vladjr/bart-base-teste2: direct link, hf CLI and curl.
- Browser
- Download file 2.11 kB
-
https://huggingface.co/vladjr/bart-base-teste2/resolve/main/README.md
- Command line
-
hf download hf://vladjr/bart-base-teste2/README.md
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curl -L -o README.md https://huggingface.co/vladjr/bart-base-teste2/resolve/main/README.md
2.11 kB
metadata
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_keras_callback
model-index:
- name: vladjr/bart-base-teste2
results: []
vladjr/bart-base-teste2
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0075
- Validation Loss: 0.0129
- Epoch: 7
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: {'inner_optimizer': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5.6e-05, 'decay_steps': 6720, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 0.2407 | 0.0360 | 0 |
| 0.0457 | 0.0178 | 1 |
| 0.0320 | 0.0169 | 2 |
| 0.0206 | 0.0133 | 3 |
| 0.0157 | 0.0250 | 4 |
| 0.0136 | 0.0165 | 5 |
| 0.0112 | 0.0169 | 6 |
| 0.0075 | 0.0129 | 7 |
Framework versions
- Transformers 4.34.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1