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jcmc
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wav2vec2-xls-r-1b-ir

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
Inference Endpoints
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+ ---
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+ language:
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+ - ga-IE
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+ license: apache-2.0
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+ tags:
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+ - automatic-speech-recognition
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+ - mozilla-foundation/common_voice_7_0
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice
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+ model-index:
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+ - name: ''
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+ results: []
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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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+ #
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - GA-IE dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Wer: 1.0
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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: 5e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 4
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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: 500
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+ - num_epochs: 100.0
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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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+ | 3.0395 | 1.94 | 500 | 3.0831 | 1.0 |
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+ | 3.0126 | 3.87 | 1000 | 2.9935 | 1.0 |
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+ | 2.9259 | 5.81 | 1500 | 2.9915 | 1.0 |
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+ | 2.9109 | 7.75 | 2000 | 2.9006 | 1.0 |
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+ | 2.8934 | 9.69 | 2500 | 2.9266 | 1.0 |
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+ | 2.9014 | 11.63 | 3000 | 2.8970 | 1.0 |
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+ | 2.8932 | 13.56 | 3500 | 2.8874 | 1.0 |
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+ | 0.0 | 15.5 | 4000 | nan | 1.0 |
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+ | 0.0 | 17.44 | 4500 | nan | 1.0 |
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+ | 0.0 | 19.38 | 5000 | nan | 1.0 |
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+ | 0.0 | 21.32 | 5500 | nan | 1.0 |
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+ | 0.0 | 23.26 | 6000 | nan | 1.0 |
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+ | 0.0 | 25.19 | 6500 | nan | 1.0 |
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+ | 0.0 | 27.13 | 7000 | nan | 1.0 |
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+ | 0.0 | 29.07 | 7500 | nan | 1.0 |
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+ | 0.0 | 31.01 | 8000 | nan | 1.0 |
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+ | 0.0 | 32.94 | 8500 | nan | 1.0 |
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+ | 0.0 | 34.88 | 9000 | nan | 1.0 |
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+ | 0.0 | 36.82 | 9500 | nan | 1.0 |
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+ | 0.0 | 38.76 | 10000 | nan | 1.0 |
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+ | 0.0 | 40.7 | 10500 | nan | 1.0 |
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+ | 0.0 | 42.63 | 11000 | nan | 1.0 |
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+ | 0.0 | 44.57 | 11500 | nan | 1.0 |
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+ | 0.0 | 46.51 | 12000 | nan | 1.0 |
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+ | 0.0 | 48.45 | 12500 | nan | 1.0 |
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+ | 0.0 | 50.39 | 13000 | nan | 1.0 |
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+ | 0.0 | 52.32 | 13500 | nan | 1.0 |
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+ | 0.0 | 54.26 | 14000 | nan | 1.0 |
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+ | 0.0 | 56.2 | 14500 | nan | 1.0 |
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+ | 0.0 | 58.14 | 15000 | nan | 1.0 |
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+ | 0.0 | 60.08 | 15500 | nan | 1.0 |
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+ | 0.0 | 62.02 | 16000 | nan | 1.0 |
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+ | 0.0 | 63.95 | 16500 | nan | 1.0 |
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+ | 0.0 | 65.89 | 17000 | nan | 1.0 |
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+ | 0.0 | 67.83 | 17500 | nan | 1.0 |
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+ | 0.0 | 69.77 | 18000 | nan | 1.0 |
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+ | 0.0 | 71.7 | 18500 | nan | 1.0 |
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+ | 0.0 | 73.64 | 19000 | nan | 1.0 |
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+ | 0.0 | 75.58 | 19500 | nan | 1.0 |
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+ | 0.0 | 77.52 | 20000 | nan | 1.0 |
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+ | 0.0 | 79.46 | 20500 | nan | 1.0 |
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+ | 0.0 | 81.39 | 21000 | nan | 1.0 |
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+ | 0.0 | 83.33 | 21500 | nan | 1.0 |
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+ | 0.0 | 85.27 | 22000 | nan | 1.0 |
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+ | 0.0 | 87.21 | 22500 | nan | 1.0 |
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+ | 0.0 | 89.15 | 23000 | nan | 1.0 |
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+ | 0.0 | 91.09 | 23500 | nan | 1.0 |
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+ | 0.0 | 93.02 | 24000 | nan | 1.0 |
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+ | 0.0 | 94.96 | 24500 | nan | 1.0 |
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+ | 0.0 | 96.9 | 25000 | nan | 1.0 |
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+ | 0.0 | 98.83 | 25500 | nan | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.16.0.dev0
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+ - Pytorch 1.10.1+cu102
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+ - Datasets 1.17.1.dev0
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+ - Tokenizers 0.11.0