metadata
license: apache-2.0
base_model: mHossain/ml_sum_v2
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ml_sum_v3
results: []
ml_sum_v3
This model is a fine-tuned version of mHossain/ml_sum_v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2395
- Rouge1: 13.9684
- Rouge2: 5.8112
- Rougel: 12.261
- Rougelsum: 13.2677
- Gen Len: 19.0
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:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 312 | 2.2395 | 13.955 | 5.7928 | 12.2638 | 13.284 | 19.0 |
| 2.6822 | 2.0 | 625 | 2.2395 | 13.9706 | 5.8212 | 12.2727 | 13.2752 | 19.0 |
| 2.6822 | 3.0 | 937 | 2.2395 | 13.9642 | 5.8154 | 12.2569 | 13.2648 | 19.0 |
| 2.658 | 3.99 | 1248 | 2.2395 | 13.9684 | 5.8112 | 12.261 | 13.2677 | 19.0 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2