cristuf/classify-clickbait-gpu

README.md

@@ -1,199 +1,76 @@
----
-library_name: transformers
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----
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-# Model Card for Model ID
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+---
+license: apache-2.0
+base_model: albert/albert-base-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: classify-clickbait-gpu
+  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. -->
+
+# classify-clickbait-gpu
+
+This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0130
+- Accuracy: 0.9976
+- F1: 0.9976
+- Precision: 0.9976
+- Recall: 0.9976
+- Accuracy Label Clickbait: 0.9933
+- Accuracy Label Factual: 1.0
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Accuracy Label Clickbait | Accuracy Label Factual |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------------------------:|:----------------------:|
+| 0.0546        | 0.4831 | 100  | 0.0504          | 0.9902   | 0.9902 | 0.9902    | 0.9902 | 0.9866                   | 0.9923                 |
+| 0.0071        | 0.9662 | 200  | 0.0060          | 0.9988   | 0.9988 | 0.9988    | 0.9988 | 0.9967                   | 1.0                    |
+| 0.0008        | 1.4493 | 300  | 0.0088          | 0.9976   | 0.9976 | 0.9976    | 0.9976 | 0.9933                   | 1.0                    |
+| 0.0006        | 1.9324 | 400  | 0.0310          | 0.9939   | 0.9939 | 0.9939    | 0.9939 | 0.9833                   | 1.0                    |
+| 0.0007        | 2.4155 | 500  | 0.0002          | 1.0      | 1.0    | 1.0       | 1.0    | 1.0                      | 1.0                    |
+| 0.0009        | 2.8986 | 600  | 0.0079          | 0.9988   | 0.9988 | 0.9988    | 0.9988 | 0.9967                   | 1.0                    |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu118
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
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+  ],
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+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "type_vocab_size": 2,
+  "vocab_size": 30000
+}

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