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T5_small_mslr2022_cochrane_finetuned
Jayicebear/T5_small_mslr2022_cochrane_finetuned
T5_small_mslr2022_cochrane_finetuned is a machine learning model from Jayicebear. 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 apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Dec 11, 2023
- Updated
- Dec 11, 2023
- SHA
- 7ba1a1fa
Base models
Datasets
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. -->
T5results
This model is a fine-tuned version of t5-small on the mslr2022 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2187
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0546 | 1.0 | 469 | 1.2336 |
| 1.0636 | 2.0 | 938 | 1.2225 |
| 1.1954 | 3.0 | 1407 | 1.2187 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.1.0
- Datasets 2.15.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Dec 11, 2023
- Updated
- Dec 11, 2023