mms_kik / README.md
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metadata
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: mms_kik
    results: []

mms_kik

This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:

  • Loss: inf
  • Wer: 0.1756

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: 0.001
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • 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
4.4384 0.1576 100 inf 0.4287
0.5264 0.3152 200 inf 0.3938
0.4716 0.4728 300 inf 0.3655
0.4084 0.6304 400 inf 0.3319
0.3953 0.7880 500 inf 0.3340
0.3605 0.9456 600 inf 0.3109
0.3601 1.1032 700 inf 0.2919
0.3368 1.2608 800 inf 0.2746
0.3102 1.4184 900 inf 0.2691
0.3209 1.5760 1000 inf 0.2602
0.2975 1.7336 1100 inf 0.2488
0.2741 1.8913 1200 inf 0.2356
0.271 2.0489 1300 inf 0.2297
0.2494 2.2065 1400 inf 0.2233
0.254 2.3641 1500 inf 0.2110
0.2484 2.5217 1600 inf 0.2117
0.2416 2.6793 1700 inf 0.2020
0.2366 2.8369 1800 inf 0.1985
0.2313 2.9945 1900 inf 0.1959
0.2228 3.1521 2000 inf 0.1897
0.2138 3.3097 2100 inf 0.1868
0.2116 3.4673 2200 inf 0.1822
0.223 3.6249 2300 inf 0.1788
0.2144 3.7825 2400 inf 0.1774
0.2131 3.9401 2500 inf 0.1756

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.0
  • Tokenizers 0.19.1