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t5-finetuned
tranquocviet226/t5-finetuned
t5-finetuned is a machine learning model from tranquocviet226. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
<<<<<<< HEAD --- libraryname: transformers license: apache-2.0 basemodel: t5-small tags: - generatedfromtrainer model-index: - name: t5-finetuned results: [] ---
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At a glance
- Model type
- t5
- Access
- Public
- Created
- Nov 26, 2024
- Updated
- Nov 27, 2024
- SHA
- b87c4111
Model card
From the Hugging Face model README
<<<<<<< HEAD
library_name: transformers license: apache-2.0 base_model: t5-small tags:
- generated_from_trainer model-index:
- name: t5-finetuned results: []
<!-- 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. -->
t5-finetuned
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2728
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.9984 | 312 | 0.3548 |
| 1.5068 | 2.0 | 625 | 0.2841 |
| 1.5068 | 2.9952 | 936 | 0.2728 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.0.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.4 =======
library_name: transformers license: apache-2.0 base_model: t5-small tags:
- generated_from_trainer model-index:
- name: t5-finetuned results: []
<!-- 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. -->
t5-finetuned
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2728
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.9984 | 312 | 0.3548 |
| 1.5068 | 2.0 | 625 | 0.2841 |
| 1.5068 | 2.9952 | 936 | 0.2728 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.0.1+cu117
- Datasets 3.1.0
- Tokenizers 0.20.4
a25bc89 (Upload fine-tuned T5 model)
- Type
- t5
- Created
- Nov 26, 2024
- Updated
- Nov 27, 2024