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Model: infinitejoy/wav2vec2-large-xls-r-300m-welsh
Source: Original Platform

README.md

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+---
+language:
+- cy
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- cy
+- generated_from_trainer
+- hf-asr-leaderboard
+- model_for_talk
+- mozilla-foundation/common_voice_7_0
+- robust-speech-event
+datasets:
+- mozilla-foundation/common_voice_7_0
+model-index:
+- name: XLS-R-300M - Welsh
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 7
+      type: mozilla-foundation/common_voice_7_0
+      args: cy
+    metrics:
+    - name: Test WER
+      type: wer
+      value: 31.003
+    - name: Test CER
+      type: cer
+      value: 7.775
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# wav2vec2-large-xls-r-300m-welsh
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - CY dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2650
+- Wer: 0.2702
+
+## 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: 7e-05
+- train_batch_size: 32
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 3000
+- num_epochs: 50.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 1.3454        | 8.2   | 3000  | 0.4926          | 0.5703 |
+| 1.1202        | 16.39 | 6000  | 0.3529          | 0.3944 |
+| 1.0058        | 24.59 | 9000  | 0.3143          | 0.3341 |
+| 0.9287        | 32.79 | 12000 | 0.2896          | 0.2980 |
+| 0.8849        | 40.98 | 15000 | 0.2727          | 0.2798 |
+| 0.8665        | 49.18 | 18000 | 0.2662          | 0.2696 |
+
+
+### Framework versions
+
+- Transformers 4.16.0.dev0
+- Pytorch 1.10.1+cu102
+- Datasets 1.18.3
+- Tokenizers 0.11.0