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Acc0.8520599250936329, F10.8500507249833522 , Augmented with bert-base-uncased.csv, finetuned on google/electra-base-discriminator

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  1. README.md +78 -0
  2. config.json +41 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/electra-base-discriminator
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: electra-base-discriminator_bert-base-uncased
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # electra-base-discriminator_bert-base-uncased
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+
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+ This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5398
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+ - Accuracy: 0.8705
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+ - F1: 0.8691
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+ - Precision: 0.8729
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+ - Recall: 0.8705
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 25
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.9217 | 1.0 | 91 | 0.8648 | 0.6459 | 0.5998 | 0.6333 | 0.6459 |
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+ | 0.5726 | 2.0 | 182 | 0.5369 | 0.8066 | 0.8064 | 0.8238 | 0.8066 |
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+ | 0.3522 | 3.0 | 273 | 0.4095 | 0.8440 | 0.8415 | 0.8477 | 0.8440 |
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+ | 0.2589 | 4.0 | 364 | 0.5367 | 0.8097 | 0.8069 | 0.8258 | 0.8097 |
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+ | 0.2718 | 5.0 | 455 | 0.4216 | 0.8612 | 0.8621 | 0.8670 | 0.8612 |
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+ | 0.164 | 6.0 | 546 | 0.5346 | 0.8612 | 0.8602 | 0.8616 | 0.8612 |
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+ | 0.1075 | 7.0 | 637 | 0.5398 | 0.8705 | 0.8691 | 0.8729 | 0.8705 |
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+ | 0.1461 | 8.0 | 728 | 0.6163 | 0.8362 | 0.8368 | 0.8442 | 0.8362 |
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+ | 0.132 | 9.0 | 819 | 0.4933 | 0.8674 | 0.8675 | 0.8701 | 0.8674 |
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+ | 0.1359 | 10.0 | 910 | 0.7141 | 0.8424 | 0.8416 | 0.8489 | 0.8424 |
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+ | 0.0971 | 11.0 | 1001 | 0.5662 | 0.8596 | 0.8578 | 0.8623 | 0.8596 |
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+ | 0.1148 | 12.0 | 1092 | 0.5685 | 0.8612 | 0.8609 | 0.8610 | 0.8612 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.0
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+ - Pytorch 2.1.2
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+ - Datasets 2.1.0
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+ - Tokenizers 0.15.1
config.json ADDED
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+ {
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+ "_name_or_path": "google/electra-base-discriminator",
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+ "architectures": [
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+ "ElectraForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "embedding_size": 768,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "LABEL_2": 2
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "electra",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "summary_activation": "gelu",
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+ "summary_last_dropout": 0.1,
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+ "summary_type": "first",
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+ "summary_use_proj": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.37.0",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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