C1_1000_1e-5_mehrdad
This model is a fine-tuned version of lnxdx/B2_1000_1e-5_hp-mehrdad on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6620
- Wer: 0.3151
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.7062 | 0.62 | 100 | 0.6594 | 0.3160 |
0.7111 | 1.25 | 200 | 0.6545 | 0.3178 |
0.7094 | 1.88 | 300 | 0.6425 | 0.3218 |
0.649 | 2.5 | 400 | 0.6549 | 0.3186 |
0.6436 | 3.12 | 500 | 0.6657 | 0.3154 |
0.6541 | 3.75 | 600 | 0.6530 | 0.3172 |
0.6317 | 4.38 | 700 | 0.6601 | 0.3151 |
0.6405 | 5.0 | 800 | 0.6589 | 0.3180 |
0.6284 | 5.62 | 900 | 0.6641 | 0.3143 |
0.6287 | 6.25 | 1000 | 0.6620 | 0.3151 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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lnxdx/B2_1000_1e-5_hp-mehrdad