wav2vec2-1b-E10_freq_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: 0.7340
  • Cer: 19.0026

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
11.3207 0.2580 200 3.4053 86.8891
1.8939 0.5160 400 1.8047 41.0303
1.1854 0.7741 600 1.4651 34.3691
0.9917 1.0321 800 1.0588 25.9516
0.744 1.2901 1000 1.1790 27.6962
0.6919 1.5481 1200 1.0604 25.9927
0.6347 1.8062 1400 0.9300 22.9323
0.5428 2.0642 1600 0.9996 24.9648
0.4724 2.3222 1800 0.9695 23.8252
0.4267 2.5802 2000 0.9463 23.7606
0.4096 2.8383 2200 0.8589 22.4448
0.3507 3.0963 2400 0.8145 20.7707
0.2874 3.3543 2600 0.8739 22.6856
0.2767 3.6123 2800 0.8657 21.8280
0.2663 3.8703 3000 0.8732 22.0630
0.2196 4.1284 3200 0.7671 19.4843
0.1867 4.3864 3400 0.7652 19.7016
0.1685 4.6444 3600 0.7288 18.7559
0.1677 4.9024 3800 0.7340 19.0026

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.3.1.post100
  • Datasets 2.19.1
  • Tokenizers 0.20.1
Downloads last month
6
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-E10_freq_speed

Finetuned
(100)
this model