End of training

README.md

@@ -5,40 +5,17 @@ tags:
 - generated_from_trainer
 datasets:
 - Nooon/Donate_a_cry
-metrics:
-- accuracy
-- f1
 model-index:
-- name: distilhubert-finetuned-Donate_a_cry-v2
-  results:
-  - task:
-      name: Audio Classification
-      type: audio-classification
-    dataset:
-      name: Donate_a_cry
-      type: Nooon/Donate_a_cry
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.8260869565217391
-    - name: F1
-      type: f1
-      value: 0.7474120082815735
+- name: distilhubert-finetuned-Donate_a_cry-v3
+  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. -->
 
-# distilhubert-finetuned-Donate_a_cry-v2
+# distilhubert-finetuned-Donate_a_cry-v3
 
 This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the Donate_a_cry dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.7098
-- Accuracy: 0.8261
-- F1: 0.7474
 
 ## Model description
 
@@ -57,34 +34,18 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- learning_rate: 0.001
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 10
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8536        | 1.0   | 52   | 0.7098          | 0.8261   | 0.7474 |
-| 0.6931        | 2.0   | 104  | 0.7021          | 0.8261   | 0.7474 |
-| 0.8844        | 3.0   | 156  | 0.6918          | 0.8261   | 0.7474 |
-| 0.4528        | 4.0   | 208  | 0.7020          | 0.8261   | 0.7474 |
-| 0.7602        | 5.0   | 260  | 0.7393          | 0.8261   | 0.7474 |
-| 0.6754        | 6.0   | 312  | 0.6792          | 0.8261   | 0.7474 |
-| 0.6515        | 7.0   | 364  | 0.6461          | 0.8261   | 0.7474 |
-| 0.3371        | 8.0   | 416  | 0.6750          | 0.8043   | 0.7455 |
-| 0.6061        | 9.0   | 468  | 0.6933          | 0.8261   | 0.7764 |
-| 0.2558        | 10.0  | 520  | 0.6946          | 0.8043   | 0.7703 |
-
-
 ### Framework versions
 
 - Transformers 4.41.2
-- Pytorch 2.3.0+cu121
-- Datasets 2.20.0
+- Pytorch 2.1.2
+- Datasets 2.19.2
 - Tokenizers 0.19.1

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