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mymodel_base_10k_sample_2e4_5epoch_batchsize4
nhantruongcse/mymodel_base_10k_sample_2e4_5epoch_batchsize4
mymodel_base_10k_sample_2e4_5epoch_batchsize4 is a machine learning model from nhantruongcse. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- t5
- Access
- Public
- Created
- Dec 10, 2023
- Updated
- Dec 10, 2023
- SHA
- 7559abad
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
mymodel_base_10k_sample
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: 2.9184
- Rouge1: 0.5671
- Rouge2: 0.2484
- Rougel: 0.3595
- Rougelsum: 0.3595
- Gen Len: 41.236
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: 0.0002
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.5062 | 1.0 | 2000 | 2.3325 | 0.5017 | 0.2092 | 0.3239 | 0.3239 | 54.9825 |
| 1.9813 | 2.0 | 4000 | 2.2335 | 0.5247 | 0.225 | 0.3379 | 0.3379 | 48.8705 |
| 1.4287 | 3.0 | 6000 | 2.2989 | 0.5466 | 0.2348 | 0.3492 | 0.3491 | 42.505 |
| 0.9458 | 4.0 | 8000 | 2.5270 | 0.5582 | 0.2476 | 0.3568 | 0.357 | 39.268 |
| 0.5884 | 5.0 | 10000 | 2.9184 | 0.5671 | 0.2484 | 0.3595 | 0.3595 | 41.236 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- mit
- Created
- Dec 10, 2023
- Updated
- Dec 10, 2023