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flan-t5-large-eng-tgl-translation
HeavenlyJoe/flan-t5-large-eng-tgl-translation
flan-t5-large-eng-tgl-translation is a machine learning model from HeavenlyJoe. 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
- Nov 22, 2023
- Updated
- Nov 22, 2023
- SHA
- d96221d1
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. -->
HeavenlyJoe/flan-t5-large-eng-tgl-translation
This model is a fine-tuned version of google/flan-t5-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3378
- Bleu: 0.4953
- Gen Len: 19.0
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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 1.9527 | 0.44 | 25 | 1.5761 | 0.2146 | 19.0 |
| 1.8866 | 0.88 | 50 | 1.5303 | 0.293 | 19.0 |
| 1.8045 | 1.32 | 75 | 1.5092 | 0.2499 | 19.0 |
| 1.7596 | 1.75 | 100 | 1.4840 | 0.3498 | 19.0 |
| 1.7354 | 2.19 | 125 | 1.4628 | 0.3282 | 19.0 |
| 1.6866 | 2.63 | 150 | 1.4437 | 0.3205 | 19.0 |
| 1.6605 | 3.07 | 175 | 1.4275 | 0.3781 | 19.0 |
| 1.6157 | 3.51 | 200 | 1.4177 | 0.3805 | 19.0 |
| 1.6237 | 3.95 | 225 | 1.4007 | 0.398 | 19.0 |
| 1.5948 | 4.39 | 250 | 1.3954 | 0.4022 | 19.0 |
| 1.5555 | 4.82 | 275 | 1.3866 | 0.3854 | 19.0 |
| 1.5388 | 5.26 | 300 | 1.3761 | 0.4105 | 19.0 |
| 1.5448 | 5.7 | 325 | 1.3712 | 0.4339 | 19.0 |
| 1.5149 | 6.14 | 350 | 1.3635 | 0.4342 | 19.0 |
| 1.5104 | 6.58 | 375 | 1.3566 | 0.459 | 19.0 |
| 1.4955 | 7.02 | 400 | 1.3525 | 0.4888 | 19.0 |
| 1.467 | 7.46 | 425 | 1.3491 | 0.4723 | 19.0 |
| 1.4872 | 7.89 | 450 | 1.3440 | 0.491 | 19.0 |
| 1.4766 | 8.33 | 475 | 1.3423 | 0.5183 | 19.0 |
| 1.4553 | 8.77 | 500 | 1.3404 | 0.5026 | 19.0 |
| 1.464 | 9.21 | 525 | 1.3384 | 0.4979 | 19.0 |
| 1.454 | 9.65 | 550 | 1.3378 | 0.4953 | 19.0 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Nov 22, 2023
- Updated
- Nov 22, 2023