metadata
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: LLM_Teached_Pegasus_50k
results: []
LLM_Teached_Pegasus_50k
This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7193
- Rouge1: 0.4541
- Rouge2: 0.2071
- Rougel: 0.3708
- Rougelsum: 0.3708
- Gen Len: 26.4531
- Precision: 0.9082
- Recall: 0.9061
- F1: 0.907
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 390 | 1.8258 | 0.4338 | 0.1906 | 0.3496 | 0.3498 | 26.2967 | 0.9049 | 0.9023 | 0.9034 |
| 2.1621 | 2.0 | 781 | 1.7537 | 0.4449 | 0.2005 | 0.3633 | 0.3633 | 26.2727 | 0.9068 | 0.9044 | 0.9054 |
| 1.8794 | 3.0 | 1172 | 1.7268 | 0.4518 | 0.2061 | 0.3696 | 0.3695 | 26.4345 | 0.9078 | 0.9058 | 0.9066 |
| 1.8271 | 3.99 | 1560 | 1.7193 | 0.4541 | 0.2071 | 0.3708 | 0.3708 | 26.4531 | 0.9082 | 0.9061 | 0.907 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0