End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: distilbert-base-uncased-finetuned-sst-2-english
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: imdb
+  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. -->
+
+# imdb
+
+This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2032
+- Accuracy: 0.927
+- Precision: 0.9241
+- Recall: 0.9318
+- F1: 0.9280
+
+## 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-06
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.2612        | 1.0   | 625  | 0.2290          | 0.9122   | 0.9080    | 0.9191 | 0.9135 |
+| 0.218         | 2.0   | 1250 | 0.2174          | 0.919    | 0.9114    | 0.9298 | 0.9205 |
+| 0.2019        | 3.0   | 1875 | 0.2120          | 0.922    | 0.9197    | 0.9263 | 0.9230 |
+| 0.1806        | 4.0   | 2500 | 0.2070          | 0.9214   | 0.9122    | 0.9342 | 0.9230 |
+| 0.1711        | 5.0   | 3125 | 0.2052          | 0.9244   | 0.9191    | 0.9322 | 0.9256 |
+| 0.1605        | 6.0   | 3750 | 0.2032          | 0.9236   | 0.9164    | 0.9338 | 0.9250 |
+| 0.1639        | 7.0   | 4375 | 0.2062          | 0.9244   | 0.9152    | 0.9370 | 0.9260 |
+| 0.1544        | 8.0   | 5000 | 0.2026          | 0.9268   | 0.9265    | 0.9287 | 0.9276 |
+| 0.148         | 9.0   | 5625 | 0.2035          | 0.9274   | 0.9212    | 0.9362 | 0.9286 |
+| 0.144         | 10.0  | 6250 | 0.2032          | 0.927    | 0.9241    | 0.9318 | 0.9280 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "distilbert-base-uncased-finetuned-sst-2-english",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "finetuning_task": "sst-2",
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "NEGATIVE",
+    "1": "POSITIVE"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "NEGATIVE": 0,
+    "POSITIVE": 1
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "output_past": true,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.44.2",
+  "vocab_size": 30522
+}

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