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Model: Plim/xls-r-300m-fr Source: Original Platform
2026-05-08 11:34:43 +08:00
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+---
+language:
+- fr
+license: apache-2.0
+tags:
+- automatic-speech-recognition
+- mozilla-foundation/common_voice_7_0
+- generated_from_trainer
+- robust-speech-event
+- hf-asr-leaderboard
+datasets:
+- mozilla-foundation/common_voice_7_0
+model-index:
+- name: XLS-R-300M - French
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 7
+      type: mozilla-foundation/common_voice_7_0
+      args: fr
+    metrics:
+    - name: Test WER
+      type: wer
+      value: 24.56
+    - name: Test CER
+      type: cer
+      value: 7.3
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Dev Data
+      type: speech-recognition-community-v2/dev_data
+      args: fr
+    metrics:
+    - name: Test WER
+      type: wer
+      value: 63.62
+    - name: Test CER
+      type: cer
+      value: 17.2
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Test Data
+      type: speech-recognition-community-v2/eval_data
+      args: fr
+    metrics:
+    - name: Test WER
+      type: wer
+      value: 66.45
+---
+---
+
+<!-- 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. -->
+
+## Model description
+
+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 - FR dataset.
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 7.5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2000
+- num_epochs: 2.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 3.495         | 0.16  | 500  | 3.3883          | 1.0    |
+| 2.9095        | 0.32  | 1000 | 2.9152          | 1.0000 |
+| 1.8434        | 0.49  | 1500 | 1.0473          | 0.7446 |
+| 1.4298        | 0.65  | 2000 | 0.5729          | 0.5130 |
+| 1.1937        | 0.81  | 2500 | 0.3795          | 0.3450 |
+| 1.1248        | 0.97  | 3000 | 0.3321          | 0.3052 |
+| 1.0835        | 1.13  | 3500 | 0.3038          | 0.2805 |
+| 1.0479        | 1.3   | 4000 | 0.2910          | 0.2689 |
+| 1.0413        | 1.46  | 4500 | 0.2798          | 0.2593 |
+| 1.014         | 1.62  | 5000 | 0.2727          | 0.2512 |
+| 1.004         | 1.78  | 5500 | 0.2646          | 0.2471 |
+| 0.9949        | 1.94  | 6000 | 0.2619          | 0.2457 |
+
+It achieves the best result on STEP 6000 on the validation set:
+- Loss: 0.2619
+- Wer: 0.2457
+
+### Framework versions
+
+- Transformers 4.17.0.dev0
+- Pytorch 1.10.2+cu102
+- Datasets 1.18.2.dev0
+- Tokenizers 0.11.0
+
+### Evaluation Commands
+1. To evaluate on `mozilla-foundation/common_voice_7` with split `test`
+
+```bash
+python eval.py --model_id Plim/xls-r-300m-fr --dataset mozilla-foundation/common_voice_7_0 --config fr --split test
+```
+
+2. To evaluate on `speech-recognition-community-v2/dev_data`
+
+```bash
+python eval.py --model_id Plim/xls-r-300m-fr --dataset speech-recognition-community-v2/dev_data --config fr --split validation --chunk_length_s 5.0 --stride_length_s 1.0
+```