End of training

README.md

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+---
+language:
+- en
+license: mit
+base_model: prajjwal1/bert-tiny
+tags:
+- pytorch
+- movie-review-sentiment
+- BertForSequenceClassification
+- generated_from_trainer
+metrics:
+- accuracy
+- matthews_correlation
+model-index:
+- name: tiny-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. -->
+
+# tiny-imdb
+
+This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the imdb dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2775
+- Accuracy: 0.8944
+- Matthews Correlation: 0.7888
+
+## 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: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 320
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 9
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Matthews Correlation |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------------------:|
+| 0.4927        | 1.0   | 1250  | 0.3557          | 0.8484   | 0.7016               |
+| 0.298         | 2.0   | 2500  | 0.2874          | 0.8866   | 0.7732               |
+| 0.2555        | 3.0   | 3750  | 0.2799          | 0.8912   | 0.7828               |
+| 0.2132        | 4.0   | 5000  | 0.2775          | 0.8944   | 0.7888               |
+| 0.1779        | 5.0   | 6250  | 0.3065          | 0.891    | 0.7835               |
+| 0.1508        | 6.0   | 7500  | 0.3331          | 0.889    | 0.7811               |
+| 0.1304        | 7.0   | 8750  | 0.3451          | 0.8926   | 0.7870               |
+| 0.119         | 8.0   | 10000 | 0.3670          | 0.8915   | 0.7852               |
+| 0.1118        | 9.0   | 11250 | 0.3655          | 0.891    | 0.7840               |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

all_results.json

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+{
+    "epoch": 9.0,
+    "eval_accuracy": 0.8944,
+    "eval_loss": 0.27750933170318604,
+    "eval_matthews_correlation": 0.788794543433118,
+    "eval_runtime": 12.4798,
+    "eval_samples_per_second": 801.293,
+    "eval_steps_per_second": 2.564
+}

config.json

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+{
+  "_name_or_path": "prajjwal1/bert-tiny",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 128,
+  "id2label": {
+    "0": "NEGATIVE",
+    "1": "POSITIVE"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 512,
+  "label2id": {
+    "NEGATIVE": 0,
+    "POSITIVE": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 2,
+  "num_hidden_layers": 2,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.35.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

evaluate_results.json

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+{
+    "epoch": 9.0,
+    "eval_accuracy": 0.8944,
+    "eval_loss": 0.27750933170318604,
+    "eval_matthews_correlation": 0.788794543433118,
+    "eval_runtime": 12.4798,
+    "eval_samples_per_second": 801.293,
+    "eval_steps_per_second": 2.564
+}

model.safetensors

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runs/Dec01_16-48-52_9e942ccf79ea/events.out.tfevents.1701449335.9e942ccf79ea.16102.0

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "normalized": false,
+      "rstrip": false,
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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