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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Dataset used to train Varsha00/t5-small-en-to-ta