End of training

README.md

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+---
+base_model: ylacombe/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-dutch-colab-CV16.0
+  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. -->
+
+# w2v-bert-2.0-dutch-colab-CV16.0
+
+This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0920
+- Wer: 0.0573
+
+## 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: 64
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- 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: 500
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 1.3106        | 1.0   | 358  | 0.1833          | 0.1350 |
+| 0.0924        | 2.0   | 716  | 0.1365          | 0.0932 |
+| 0.0521        | 3.0   | 1074 | 0.1121          | 0.0732 |
+| 0.033         | 3.99  | 1432 | 0.0957          | 0.0619 |
+| 0.0221        | 4.99  | 1790 | 0.0920          | 0.0573 |
+
+
+### Framework versions
+
+- Transformers 4.37.0.dev0
+- Pytorch 1.12.1+cu116
+- Datasets 2.4.0
+- Tokenizers 0.15.2