metadata
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mymodel_base_10k_sample_2e5_v2
results: []
mymodel_base_10k_sample_2e5_v2
This model is a fine-tuned version of VietAI/vit5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8988
- Rouge1: 0.5793
- Rouge2: 0.2711
- Rougel: 0.3756
- Rougelsum: 0.3756
- Gen Len: 39.782
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.9788 | 1.0 | 2000 | 1.8380 | 0.5644 | 0.2515 | 0.3604 | 0.3603 | 42.489 |
| 1.7232 | 2.0 | 4000 | 1.8040 | 0.5665 | 0.2592 | 0.3675 | 0.3674 | 39.2215 |
| 1.5036 | 3.0 | 6000 | 1.8337 | 0.5682 | 0.26 | 0.3674 | 0.3674 | 38.9015 |
| 1.3468 | 4.0 | 8000 | 1.8675 | 0.5728 | 0.2664 | 0.3706 | 0.3707 | 38.9095 |
| 1.2546 | 5.0 | 10000 | 1.8988 | 0.5793 | 0.2711 | 0.3756 | 0.3756 | 39.782 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0