This model is a fine-tuned version of CohereLabs/cohere-transcribe-03-2026 on the jssaluja/rajinder_singh_corrected dataset. It achieves the following results on the evaluation set:

Loss: 0.6960
Wer: 0.8061
Cer: 0.6250
Ccer: 0.6463
Ncer: 0.6057

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 14
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer	Ccer	Ncer
0.5394	1.0	299	0.2230	0.5136	0.2439	0.2622	0.2115
0.0748	2.0	598	0.3855	0.5641	0.3862	0.4109	0.3539

Framework versions

Transformers 5.15.1
Pytorch 2.13.0+cu130
Datasets 5.0.1
Tokenizers 0.22.2

jssaluja/cohere-transcribe-punjabi-ccer-train-113953-epochs-10-test-1569

jssaluja/cohere-transcribe-punjabi-ncer-train-60381-epochs-2-small

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

jssaluja/
cohere-transcribe-punjabi-ccer-train-113953-epochs-10-test-1569