End of training

README.md

@@ -0,0 +1,66 @@
+---
+license: apache-2.0
+base_model: google/efficientnet-b6
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: DeepFake-EN-B6
+  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. -->
+
+# DeepFake-EN-B6
+
+This model is a fine-tuned version of [google/efficientnet-b6](https://huggingface.co/google/efficientnet-b6) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0036
+- Accuracy: 0.9989
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2.5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.0076        | 0.9998 | 2187 | 0.0088          | 0.9970   |
+| 0.002         | 2.0    | 4375 | 0.0173          | 0.9931   |
+| 0.0011        | 2.4997 | 5468 | 0.0036          | 0.9989   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.1.2
+- Datasets 2.19.2
+- Tokenizers 0.19.1

all_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 2.499657142857143,
+    "eval_accuracy": 0.9988666666666667,
+    "eval_loss": 0.0036366877611726522,
+    "eval_runtime": 590.1134,
+    "eval_samples_per_second": 50.838,
+    "eval_steps_per_second": 1.59
+}

eval_results.json

@@ -0,0 +1,8 @@
+{
+    "epoch": 2.499657142857143,
+    "eval_accuracy": 0.9988666666666667,
+    "eval_loss": 0.0036366877611726522,
+    "eval_runtime": 590.1134,
+    "eval_samples_per_second": 50.838,
+    "eval_steps_per_second": 1.59
+}