End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: wav2vec2-finetune-XLSR_maroc
+  results: []
+---
+
+<!-- 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-finetune-XLSR_maroc
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2804
+- Wer: 0.3265
+
+## 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: 0.0003
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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: 500
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 4.9859        | 0.83  | 400   | 2.0919          | 0.9982 |
+| 0.8639        | 1.66  | 800   | 0.4365          | 0.5925 |
+| 0.4879        | 2.49  | 1200  | 0.3467          | 0.5079 |
+| 0.3732        | 3.32  | 1600  | 0.3267          | 0.4756 |
+| 0.314         | 4.15  | 2000  | 0.2835          | 0.4314 |
+| 0.274         | 4.97  | 2400  | 0.2915          | 0.4364 |
+| 0.2463        | 5.8   | 2800  | 0.3050          | 0.4277 |
+| 0.2354        | 6.63  | 3200  | 0.2766          | 0.4179 |
+| 0.2101        | 7.46  | 3600  | 0.2896          | 0.4071 |
+| 0.1976        | 8.29  | 4000  | 0.2856          | 0.4099 |
+| 0.186         | 9.12  | 4400  | 0.2849          | 0.3987 |
+| 0.1758        | 9.95  | 4800  | 0.2819          | 0.4026 |
+| 0.1667        | 10.78 | 5200  | 0.2869          | 0.3934 |
+| 0.1508        | 11.61 | 5600  | 0.2793          | 0.3851 |
+| 0.1468        | 12.44 | 6000  | 0.2777          | 0.3836 |
+| 0.1322        | 13.26 | 6400  | 0.2731          | 0.3767 |
+| 0.1295        | 14.09 | 6800  | 0.2833          | 0.3741 |
+| 0.1157        | 14.92 | 7200  | 0.2815          | 0.3786 |
+| 0.1147        | 15.75 | 7600  | 0.2684          | 0.3741 |
+| 0.1099        | 16.58 | 8000  | 0.2704          | 0.3677 |
+| 0.1056        | 17.41 | 8400  | 0.2744          | 0.3668 |
+| 0.0983        | 18.24 | 8800  | 0.2675          | 0.3676 |
+| 0.0975        | 19.07 | 9200  | 0.2787          | 0.3588 |
+| 0.0906        | 19.9  | 9600  | 0.2749          | 0.3537 |
+| 0.0862        | 20.73 | 10000 | 0.2875          | 0.3557 |
+| 0.0812        | 21.55 | 10400 | 0.2863          | 0.3482 |
+| 0.0761        | 22.38 | 10800 | 0.2739          | 0.3513 |
+| 0.0738        | 23.21 | 11200 | 0.2878          | 0.3467 |
+| 0.0678        | 24.04 | 11600 | 0.2886          | 0.3399 |
+| 0.0661        | 24.87 | 12000 | 0.2958          | 0.3380 |
+| 0.0623        | 25.7  | 12400 | 0.2779          | 0.3354 |
+| 0.0586        | 26.53 | 12800 | 0.2871          | 0.3333 |
+| 0.0563        | 27.36 | 13200 | 0.2895          | 0.3316 |
+| 0.0554        | 28.19 | 13600 | 0.2846          | 0.3277 |
+| 0.0522        | 29.02 | 14000 | 0.2752          | 0.3276 |
+| 0.0498        | 29.84 | 14400 | 0.2804          | 0.3265 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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