afaji/summerschool-bert-massive

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: summerschool-bert-massive
+  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. -->
+
+# summerschool-bert-massive
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8479
+- Accuracy: 0.8283
+- F1: 0.8139
+
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
+| 3.8604        | 0.1389 | 100  | 3.3964          | 0.2720   | 0.2091 |
+| 3.046         | 0.2778 | 200  | 2.5353          | 0.4870   | 0.3971 |
+| 2.3977        | 0.4167 | 300  | 2.0141          | 0.6193   | 0.5592 |
+| 1.9293        | 0.5556 | 400  | 1.6738          | 0.6803   | 0.6328 |
+| 1.6997        | 0.6944 | 500  | 1.4307          | 0.7334   | 0.6937 |
+| 1.505         | 0.8333 | 600  | 1.2759          | 0.7772   | 0.7469 |
+| 1.3531        | 0.9722 | 700  | 1.1656          | 0.7757   | 0.7445 |
+| 1.1651        | 1.1111 | 800  | 1.0720          | 0.7914   | 0.7707 |
+| 1.0441        | 1.25   | 900  | 0.9979          | 0.8032   | 0.7838 |
+| 1.0021        | 1.3889 | 1000 | 0.9496          | 0.8146   | 0.7977 |
+| 0.9732        | 1.5278 | 1100 | 0.8996          | 0.8278   | 0.8116 |
+| 0.9025        | 1.6667 | 1200 | 0.8816          | 0.8214   | 0.8053 |
+| 0.8952        | 1.8056 | 1300 | 0.8612          | 0.8273   | 0.8128 |
+| 0.8435        | 1.9444 | 1400 | 0.8479          | 0.8283   | 0.8139 |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
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+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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special_tokens_map.json

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

tokenizer_config.json

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+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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