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README.md

@@ -4,26 +4,9 @@ license: apache-2.0
 base_model: ntu-spml/distilhubert
 tags:
 - generated_from_trainer
-datasets:
-- audiofolder
-metrics:
-- accuracy
 model-index:
 - name: distilhubert-finetuned-cry-detector
-  results:
-  - task:
-      name: Audio Classification
-      type: audio-classification
-    dataset:
-      name: audiofolder
-      type: audiofolder
-      config: default
-      split: train
-      args: default
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.9926739926739927
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,10 +14,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # distilhubert-finetuned-cry-detector
 
-This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0459
-- Accuracy: 0.9927
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on an unknown dataset.
 
 ## Model description
 
@@ -62,26 +42,17 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.001
-- num_epochs: 10
+- num_epochs: 1
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
-|:-------------:|:------:|:----:|:---------------:|:--------:|
-| No log        | 0.9956 | 85   | 0.0692          | 0.9773   |
-| No log        | 1.9912 | 170  | 0.0466          | 0.9861   |
-| No log        | 2.9985 | 256  | 0.0489          | 0.9853   |
-| No log        | 3.9941 | 341  | 0.0423          | 0.9897   |
-| No log        | 4.9898 | 426  | 0.0443          | 0.9919   |
-| 0.055         | 5.9971 | 512  | 0.0434          | 0.9927   |
-| 0.055         | 6.9927 | 597  | 0.0440          | 0.9927   |
-| 0.055         | 8.0    | 683  | 0.0460          | 0.9927   |
-| 0.055         | 8.9956 | 768  | 0.0459          | 0.9927   |
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 0.9956 | 85   | 0.1412          | 0.9480   | 0.9478    | 0.9480 | 0.9476 |
 
 
 ### Framework versions
 
 - Transformers 4.44.2
-- Pytorch 2.4.0+cu121
-- Datasets 2.21.0
+- Pytorch 2.4.1+cu121
 - Tokenizers 0.19.1

checkpoint-85/config.json

@@ -45,6 +45,7 @@
   "feat_proj_dropout": 0.0,
   "feat_proj_layer_norm": false,
   "final_dropout": 0.0,
+  "finetuning_task": "audio-classification",
   "hidden_act": "gelu",
   "hidden_dropout": 0.1,
   "hidden_size": 768,
@@ -55,8 +56,8 @@
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "crying": "0",
-    "no_crying": "1"
+    "crying": 0,
+    "no_crying": 1
   },
   "layer_norm_eps": 1e-05,
   "layerdrop": 0.0,

checkpoint-85/model.safetensors

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checkpoint-85/optimizer.pt

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checkpoint-85/scheduler.pt

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checkpoint-85/trainer_state.json

@@ -1,5 +1,5 @@
 {
-  "best_metric": 0.9772893772893773,
+  "best_metric": 0.947985347985348,
   "best_model_checkpoint": "distilhubert-finetuned-cry-detector/checkpoint-85",
   "epoch": 0.9956076134699854,
   "eval_steps": 500,
@@ -10,18 +10,21 @@
   "log_history": [
     {
       "epoch": 0.9956076134699854,
-      "eval_accuracy": 0.9772893772893773,
-      "eval_loss": 0.06922276318073273,
-      "eval_runtime": 15.5305,
-      "eval_samples_per_second": 87.892,
-      "eval_steps_per_second": 11.011,
+      "eval_accuracy": 0.947985347985348,
+      "eval_f1": 0.947604288263629,
+      "eval_loss": 0.14118361473083496,
+      "eval_precision": 0.9477540003855793,
+      "eval_recall": 0.947985347985348,
+      "eval_runtime": 5.9376,
+      "eval_samples_per_second": 229.892,
+      "eval_steps_per_second": 28.8,
       "step": 85
     }
   ],
   "logging_steps": 500,
-  "max_steps": 850,
+  "max_steps": 85,
   "num_input_tokens_seen": 0,
-  "num_train_epochs": 10,
+  "num_train_epochs": 1,
   "save_steps": 500,
   "stateful_callbacks": {
     "EarlyStoppingCallback": {
@@ -39,12 +42,12 @@
         "should_evaluate": false,
         "should_log": false,
         "should_save": true,
-        "should_training_stop": false
+        "should_training_stop": true
       },
       "attributes": {}
     }
   },
-  "total_flos": 1.241700759936e+16,
+  "total_flos": 1.237152405504e+16,
   "train_batch_size": 8,
   "trial_name": null,
   "trial_params": null

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config.json

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   "feat_proj_dropout": 0.0,
   "feat_proj_layer_norm": false,
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   "hidden_act": "gelu",
   "hidden_dropout": 0.1,
   "hidden_size": 768,
@@ -55,8 +56,8 @@
   "initializer_range": 0.02,
   "intermediate_size": 3072,
   "label2id": {
-    "crying": "0",
-    "no_crying": "1"
+    "crying": 0,
+    "no_crying": 1
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   "layer_norm_eps": 1e-05,
   "layerdrop": 0.0,

model.safetensors

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runs/Sep08_19-39-26_ubumarcos/events.out.tfevents.1725817167.ubumarcos

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training_args.bin

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