tamil-finetuning
This model is a fine-tuned version of t5-small on the samanantar dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.3531
- eval_bleu: 14.4184
- eval_gen_len: 32.6451
- eval_runtime: 7195.8762
- eval_samples_per_second: 2.223
- eval_steps_per_second: 2.223
- epoch: 2.0
- step: 8000
Model description
t5-small finetuned for translation in en-ta
Intended uses & limitations
More information needed
Training and evaluation data
ai4bharath/samanantar -> 80-20 split
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- 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
- num_epochs: 3
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Varsha00/t5-small-en-to-ta
Base model
google-t5/t5-small