End of training

README.md

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+---
+library_name: transformers
+language:
+- gn
+license: apache-2.0
+base_model: glob-asr/wav2vec2-large-xls-r-300m-guarani-small
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_16_1
+metrics:
+- wer
+model-index:
+- name: Common Voice 16
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 16
+      type: mozilla-foundation/common_voice_16_1
+      config: gn
+      split: None
+      args: gn
+    metrics:
+    - name: Wer
+      type: wer
+      value: 49.7001998667555
+---
+
+<!-- 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. -->
+
+# Common Voice 16
+
+This model is a fine-tuned version of [glob-asr/wav2vec2-large-xls-r-300m-guarani-small](https://huggingface.co/glob-asr/wav2vec2-large-xls-r-300m-guarani-small) on the Common Voice 16 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4335
+- Wer: 49.7002
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant_with_warmup
+- lr_scheduler_warmup_steps: 3000
+- training_steps: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 1.258         | 0.4955 | 500  | 0.3710          | 53.1646 |
+| 0.921         | 0.9911 | 1000 | 0.3282          | 49.2338 |
+| 0.7458        | 1.4866 | 1500 | 0.2940          | 46.7022 |
+| 0.6763        | 1.9822 | 2000 | 0.2628          | 44.9700 |
+| 0.568         | 2.4777 | 2500 | 0.2616          | 43.3711 |
+| 0.5414        | 2.9732 | 3000 | 0.2504          | 39.8401 |
+| 0.484         | 3.4688 | 3500 | 0.2462          | 41.0393 |
+| 0.5281        | 3.9643 | 4000 | 0.3584          | 43.5043 |
+| 0.5756        | 4.4599 | 4500 | 0.4220          | 44.3038 |
+| 0.721         | 4.9554 | 5000 | 0.4335          | 49.7002 |
+
+
+### Framework versions
+
+- Transformers 4.44.1
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

model.safetensors

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