test_pelby_v2 / README.md
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metadata
base_model: Osolon/wav2vec2-large-xls-r-300m-pl
library_name: transformers
license: apache-2.0
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: wav2vec2-full_v2
    results: []

wav2vec2-full_v2

This model is a fine-tuned version of Osolon/wav2vec2-large-xls-r-300m-pl on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: inf
  • Wer: 0.2842

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: 8
  • eval_batch_size: 4
  • 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: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2498 0.1241 400 inf 0.2197
0.2049 0.2481 800 inf 0.1586
0.1798 0.3722 1200 inf 0.1380
0.1527 0.4963 1600 inf 0.1344
0.1588 0.6203 2000 inf 0.1336
0.1401 0.7444 2400 inf 0.1168
0.1336 0.8685 2800 inf 0.1064
0.1308 0.9926 3200 inf 0.0983
0.1177 1.1166 3600 inf 0.0911
0.1261 1.2407 4000 inf 0.0878
0.2208 1.3648 4400 inf 0.1019
0.2814 1.4888 4800 inf 0.1836
0.4642 1.6129 5200 inf 0.2173
0.6645 1.7370 5600 inf 0.6257
0.8667 1.8610 6000 inf 0.7893
0.7724 1.9851 6400 inf 0.7634
0.6747 2.1092 6800 inf 0.5521
0.5989 2.2333 7200 inf 0.5029
0.5234 2.3573 7600 inf 0.4523
0.4844 2.4814 8000 inf 0.3895
0.4708 2.6055 8400 inf 0.3319
0.4701 2.7295 8800 inf 0.2781
0.4665 2.8536 9200 inf 0.2713
0.4652 2.9777 9600 inf 0.2844
0.4539 3.1017 10000 inf 0.2842
0.4692 3.2258 10400 inf 0.2842
0.4658 3.3499 10800 inf 0.2842
0.4602 3.4739 11200 inf 0.2842
0.4648 3.5980 11600 inf 0.2842
0.4608 3.7221 12000 inf 0.2842
0.4677 3.8462 12400 inf 0.2842
0.4731 3.9702 12800 inf 0.2842

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1