Edit model card

Wave2Vec2-Bert2.0 - Kiran Pantha

This model is a fine-tuned version of kiranpantha/w2v-bert-2.0-nepali on the OpenSLR54 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4058
  • Wer: 0.4307

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.7246 0.15 300 0.5189 0.5402
0.6721 0.3 600 0.6084 0.5423
0.6956 0.45 900 0.5712 0.5412
0.6341 0.6 1200 0.4997 0.5105
0.6119 0.75 1500 0.5008 0.5148
0.564 0.9 1800 0.4627 0.4793
0.5416 1.05 2100 0.4767 0.4734
0.4569 1.2 2400 0.4754 0.4651
0.4768 1.35 2700 0.4420 0.4702
0.438 1.5 3000 0.4563 0.4614
0.4337 1.65 3300 0.4290 0.4543
0.447 1.8 3600 0.4081 0.4392
0.4108 1.95 3900 0.4058 0.4307

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1
Downloads last month
17
Safetensors
Model size
606M params
Tensor type
F32
·
Inference Examples
Inference API (serverless) is not available, repository is disabled.

Model tree for kiranpantha/w2v-bert-2.0-nepali-iteration-test

Finetuned
this model

Evaluation results