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mt5-base-ICFOSS-malayalam_Hindi_Translator
ArunIcfoss/mt5-base-ICFOSS-malayalam_Hindi_Translator
mt5-base-ICFOSS-malayalam_Hindi_Translator is a machine learning model from ArunIcfoss. 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 peft. 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
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Aug 19, 2024
- Updated
- Aug 19, 2024
- SHA
- 853a67a5
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. -->
mt5-base-ICFOSS-malayalam_Hindi_Translator
This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2179
- Bleu: 6.2035
- Rouge: {'rouge1': 0.2667970960136926, 'rouge2': 0.14574925525428614, 'rougeL': 0.26511828595423204, 'rougeLsum': 0.26501665904942706}
- Chrf: {'score': 23.454551827072866, 'char_order': 6, 'word_order': 0, 'beta': 2}
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Rouge | Chrf |
|---|---|---|---|---|---|---|
| 2.5515 | 1.0 | 4315 | 1.2874 | 5.8306 | {'rouge1': 0.2660910934739513, 'rouge2': 0.14404792849379128, 'rougeL': 0.26384549634107013, 'rougeLsum': 0.2637751499455684} | {'score': 22.571342084258088, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 1.9143 | 2.0 | 8630 | 1.2319 | 6.1128 | {'rouge1': 0.263256301663898, 'rouge2': 0.14256738224583015, 'rougeL': 0.261282034035635, 'rougeLsum': 0.2613517649673947} | {'score': 23.235214776547263, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 1.8644 | 3.0 | 12945 | 1.2192 | 6.2145 | {'rouge1': 0.2670714744552978, 'rouge2': 0.14606073298261613, 'rougeL': 0.2652594809906982, 'rougeLsum': 0.26489596193447795} | {'score': 23.438449086905997, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 1.8539 | 4.0 | 17260 | 1.2179 | 6.2043 | {'rouge1': 0.26678061058524805, 'rouge2': 0.14565482302690236, 'rougeL': 0.26489350144733725, 'rougeLsum': 0.26477198178581135} | {'score': 23.464895899326955, 'char_order': 6, 'word_order': 0, 'beta': 2} |
| 1.8525 | 5.0 | 21575 | 1.2179 | 6.2035 | {'rouge1': 0.2667970960136926, 'rouge2': 0.14574925525428614, 'rougeL': 0.26511828595423204, 'rougeLsum': 0.26501665904942706} | {'score': 23.454551827072866, 'char_order': 6, 'word_order': 0, 'beta': 2} |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Library
- peft
- License
- apache-2.0
- Created
- Aug 19, 2024
- Updated
- Aug 19, 2024