Edit model card

xls-r-1b-bem-natbed-non-native-model

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the NATBED - BEM dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6818
  • Wer: 0.7142

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: 0.0003
  • 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: 100
  • num_epochs: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.8975 0.4515 100 1.1343 0.9316
1.0247 0.9029 200 0.9811 0.8826
0.9631 1.3544 300 0.8108 0.7524
0.8711 1.8059 400 0.7749 0.7638
0.7935 2.2573 500 0.8008 0.8232
0.7869 2.7088 600 0.7334 0.7262
0.7265 3.1603 700 0.7239 0.6950
0.7011 3.6117 800 0.7077 0.6807
0.7343 4.0632 900 0.6985 0.6914
0.6624 4.5147 1000 0.6818 0.7142
0.6642 4.9661 1100 0.7097 0.6968
0.6064 5.4176 1200 0.7195 0.6856
0.5867 5.8691 1300 0.6899 0.6880

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0
Downloads last month
0
Safetensors
Model size
963M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for csikasote/xls-r-1b-bem-natbed-non-native-model

Finetuned
(30)
this model