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mt5-budget-seq2seq-2
napatswift/mt5-budget-seq2seq-2
mt5-budget-seq2seq-2 is a machine learning model from napatswift. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- t5
- Access
- Public
- Created
- Oct 6, 2023
- Updated
- Oct 7, 2023
- SHA
- 3b2d1837
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. -->
mt5-budget-seq2seq-2
This model is a fine-tuned version of napatswift/mt5-budget-seq-1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0056
- Cer: 0.7435
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: 0.0006
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- 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: 90
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Cer | Validation Loss |
|---|---|---|---|---|
| 0.0215 | 0.34 | 400 | 0.5769 | 0.0073 |
| 0.0142 | 2.12 | 800 | 0.0072 | 0.7436 |
| 0.0091 | 3.18 | 1200 | 0.0070 | 0.7436 |
| 0.006 | 4.24 | 1600 | 0.0056 | 0.7435 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0
- Library
- transformers
- Type
- t5
- Languages
- th, en
- Created
- Oct 6, 2023
- Updated
- Oct 7, 2023