End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-conformer-rel-pos-large
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: wav2vec2-conformer-rel-pos-large-medical-intent-v2
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6169590643274854
+    - name: Precision
+      type: precision
+      value: 0.6350528050296339
+    - name: Recall
+      type: recall
+      value: 0.6169590643274854
+---
+
+<!-- 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-conformer-rel-pos-large-medical-intent-v2
+
+This model is a fine-tuned version of [facebook/wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0410
+- Accuracy: 0.6170
+- Precision: 0.6351
+- Recall: 0.6170
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
+| 1.7714        | 1.0   | 82   | 1.7605          | 0.2339   | 0.3198    | 0.2339 |
+| 1.511         | 2.0   | 164  | 1.5148          | 0.4298   | 0.3817    | 0.4298 |
+| 1.1417        | 2.99  | 246  | 1.1530          | 0.5936   | 0.6491    | 0.5936 |
+| 0.8747        | 3.99  | 328  | 1.0410          | 0.6170   | 0.6351    | 0.6170 |
+
+
+### Framework versions
+
+- Transformers 4.39.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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