metadata
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LLM_Teached_Bart
results: []
LLM_Teached_Bart
This model is a fine-tuned version of facebook/bart-large-xsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6256
- Rouge1: 0.4761
- Rouge2: 0.2113
- Rougel: 0.3732
- Rougelsum: 0.3731
- Gen Len: 41.0064
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:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
1.6549 | 1.0 | 1250 | 1.6621 | 0.4696 | 0.2069 | 0.3636 | 0.3636 | 42.6855 |
1.2925 | 2.0 | 2500 | 1.6256 | 0.4761 | 0.2113 | 0.3732 | 0.3731 | 41.0064 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0