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continue_grammar_model_wmt460
mika5883/continue_grammar_model_wmt460
continue_grammar_model_wmt460 is a machine learning model from mika5883. 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
- Mar 25, 2024
- Updated
- Mar 25, 2024
- SHA
- 08cc080b
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. -->
continue_grammar_model_wmt460
This model is a fine-tuned version of mika5883/grammar_model_wmt460 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3223
- Bleu: 57.4683
- Gen Len: 16.2348
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.4944 | 1.0 | 983 | 0.3219 | 57.5404 | 16.2288 |
| 0.4715 | 2.0 | 1966 | 0.3223 | 57.4683 | 16.2348 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- t5
- Created
- Mar 25, 2024
- Updated
- Mar 25, 2024