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wav2vec2-large-xls-r-300m-gn-pt

Automatic Speech Recognition
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wav2vec2
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  1. README.md +122 -0
  2. model.safetensors +1 -1
  3. runs/Nov02_18-53-57_38d2530731df/events.out.tfevents.1698951552.38d2530731df.355.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-xls-r-300m
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_13_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-large-xls-r-300m-gn-pt
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: common_voice_13_0
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+ type: common_voice_13_0
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+ config: gn
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+ split: test
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+ args: gn
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.5431804645622395
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # wav2vec2-large-xls-r-300m-gn-pt
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6822
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+ - Wer: 0.5432
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 35
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 4.1972 | 0.79 | 400 | 1.9288 | 1.0045 |
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+ | 0.9928 | 1.58 | 800 | 0.8247 | 0.9452 |
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+ | 0.6075 | 2.36 | 1200 | 0.7675 | 0.8451 |
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+ | 0.4724 | 3.15 | 1600 | 0.5485 | 0.7111 |
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+ | 0.3879 | 3.94 | 2000 | 0.5885 | 0.7433 |
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+ | 0.3152 | 4.73 | 2400 | 0.7606 | 0.7695 |
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+ | 0.2872 | 5.52 | 2800 | 0.5723 | 0.6608 |
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+ | 0.258 | 6.31 | 3200 | 0.5971 | 0.6820 |
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+ | 0.2317 | 7.09 | 3600 | 0.5845 | 0.6471 |
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+ | 0.2137 | 7.88 | 4000 | 0.7690 | 0.7198 |
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+ | 0.193 | 8.67 | 4400 | 0.6219 | 0.6614 |
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+ | 0.1795 | 9.46 | 4800 | 0.6203 | 0.6703 |
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+ | 0.1768 | 10.25 | 5200 | 0.5645 | 0.6164 |
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+ | 0.1637 | 11.03 | 5600 | 0.5804 | 0.6412 |
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+ | 0.1573 | 11.82 | 6000 | 0.5914 | 0.5896 |
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+ | 0.1467 | 12.61 | 6400 | 0.6517 | 0.6200 |
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+ | 0.141 | 13.4 | 6800 | 0.6376 | 0.6310 |
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+ | 0.135 | 14.19 | 7200 | 0.6343 | 0.6042 |
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+ | 0.1279 | 14.98 | 7600 | 0.6680 | 0.6325 |
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+ | 0.1222 | 15.76 | 8000 | 0.7109 | 0.6617 |
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+ | 0.1169 | 16.55 | 8400 | 0.7067 | 0.6361 |
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+ | 0.114 | 17.34 | 8800 | 0.7143 | 0.6144 |
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+ | 0.1085 | 18.13 | 9200 | 0.6871 | 0.6081 |
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+ | 0.0996 | 18.92 | 9600 | 0.8332 | 0.6569 |
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+ | 0.0952 | 19.7 | 10000 | 0.7076 | 0.5992 |
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+ | 0.0929 | 20.49 | 10400 | 0.6946 | 0.6078 |
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+ | 0.0871 | 21.28 | 10800 | 0.6197 | 0.5822 |
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+ | 0.0823 | 22.07 | 11200 | 0.6969 | 0.5876 |
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+ | 0.0776 | 22.86 | 11600 | 0.6285 | 0.5619 |
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+ | 0.0758 | 23.65 | 12000 | 0.7098 | 0.6010 |
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+ | 0.0728 | 24.43 | 12400 | 0.6618 | 0.5905 |
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+ | 0.0664 | 25.22 | 12800 | 0.6484 | 0.5536 |
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+ | 0.0656 | 26.01 | 13200 | 0.6417 | 0.5593 |
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+ | 0.0603 | 26.8 | 13600 | 0.7287 | 0.5813 |
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+ | 0.0571 | 27.59 | 14000 | 0.6727 | 0.5700 |
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+ | 0.0559 | 28.37 | 14400 | 0.6775 | 0.5631 |
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+ | 0.0555 | 29.16 | 14800 | 0.7849 | 0.5968 |
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+ | 0.0506 | 29.95 | 15200 | 0.8266 | 0.6185 |
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+ | 0.0485 | 30.74 | 15600 | 0.7347 | 0.5747 |
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+ | 0.0461 | 31.53 | 16000 | 0.6836 | 0.5432 |
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+ | 0.0423 | 32.32 | 16400 | 0.6913 | 0.5396 |
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+ | 0.0407 | 33.1 | 16800 | 0.6655 | 0.5328 |
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+ | 0.04 | 33.89 | 17200 | 0.6873 | 0.5399 |
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+ | 0.0396 | 34.68 | 17600 | 0.6822 | 0.5432 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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