wav2vec2-1b-E50_speed

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

  • Loss: 0.5794
  • Cer: 21.1466

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: 2
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 8
  • 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: 50
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
22.602 0.2580 200 6.2336 100.0
4.8547 0.5160 400 4.5853 98.3318
4.6154 0.7741 600 4.6172 93.2331
4.4727 1.0321 800 4.3835 80.8506
4.2854 1.2901 1000 4.2819 77.9194
3.947 1.5481 1200 3.1503 61.7070
2.091 1.8062 1400 1.7032 40.4547
1.223 2.0642 1600 1.4472 39.8320
0.8867 2.3222 1800 1.2054 30.8506
0.7444 2.5802 2000 1.0326 31.4732
0.6529 2.8383 2200 0.8416 27.4671
0.5313 3.0963 2400 0.8239 25.0176
0.4148 3.3543 2600 0.7047 24.6417
0.3665 3.6123 2800 0.6761 22.5681
0.3435 3.8703 3000 0.6632 22.3567
0.2865 4.1284 3200 0.5879 21.1936
0.2307 4.3864 3400 0.6009 21.3875
0.2198 4.6444 3600 0.5810 21.2700
0.195 4.9024 3800 0.5794 21.1466

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.3.1.post100
  • Datasets 2.19.1
  • Tokenizers 0.20.1
Downloads last month
5
Safetensors
Model size
964M 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 Gummybear05/wav2vec2-1b-E50_speed

Finetuned
(100)
this model