IndicBART_new
This model is a fine-tuned version of ai4bharat/IndicBART on the None dataset. It achieves the following results on the evaluation set:
- Loss: 4.1132
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.96 | 11 | 6.1880 |
No log | 2.0 | 23 | 5.8543 |
No log | 2.96 | 34 | 5.4336 |
No log | 4.0 | 46 | 4.9778 |
No log | 4.96 | 57 | 4.6550 |
No log | 6.0 | 69 | 4.3842 |
No log | 6.96 | 80 | 4.1987 |
No log | 7.65 | 88 | 4.1132 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.2
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