wav2vec2-1b-E30_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: 0.5758
  • Cer: 14.7028

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
16.6326 0.2580 200 4.7434 100.0
4.6388 0.5160 400 3.9414 88.5926
2.026 0.7741 600 1.7935 41.2711
1.1754 1.0321 800 1.2455 29.8990
0.8337 1.2901 1000 1.0037 25.8047
0.7399 1.5481 1200 0.9414 23.3846
0.6535 1.8062 1400 0.8053 21.4344
0.544 2.0642 1600 0.9218 23.1673
0.4264 2.3222 1800 0.8181 20.7354
0.387 2.5802 2000 0.7663 19.5900
0.3623 2.8383 2200 0.7863 20.2420
0.3416 3.0963 2400 0.8668 22.5975
0.2731 3.3543 2600 0.7251 18.6501
0.2394 3.6123 2800 0.6185 16.2183
0.2255 3.8703 3000 0.5926 15.5839
0.1874 4.1284 3200 0.5889 15.3900
0.1549 4.3864 3400 0.5765 15.1375
0.1514 4.6444 3600 0.5856 14.8614
0.1424 4.9024 3800 0.5758 14.7028

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-E30_speed

Finetuned
(100)
this model