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summarization_finetuned
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 1.5478
- Validation Loss: 1.4195
- Train Rougel: tf.Tensor(0.29894578, shape=(), dtype=float32)
- Epoch: 0
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': 'Adamax', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Rougel | Epoch |
|---|---|---|---|
| 1.5478 | 1.4195 | tf.Tensor(0.29894578, shape=(), dtype=float32) | 0 |
Framework versions
- Transformers 4.25.1
- TensorFlow 2.10.0
- Datasets 2.6.1
- Tokenizers 0.12.1
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("akum1343/summarization_finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("akum1343/summarization_finetuned")