Saving best model of SciBERT_twowayloss_25K_bs64 to hub

README.md

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+---
+base_model: allenai/scibert_scivocab_uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: SciBERT_twowayloss_25K_bs64
+  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. -->
+
+# SciBERT_twowayloss_25K_bs64
+
+This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0158
+- Accuracy: 0.9945
+- Precision: 0.7948
+- Recall: 0.5830
+- F1: 0.6727
+- Hamming: 0.0055
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 25000
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
+| 0.0332        | 0.16  | 5000  | 0.0283          | 0.9921   | 0.8249    | 0.2410 | 0.3730 | 0.0079  |
+| 0.0195        | 0.32  | 10000 | 0.0186          | 0.9939   | 0.7964    | 0.4983 | 0.6131 | 0.0061  |
+| 0.0173        | 0.47  | 15000 | 0.0168          | 0.9943   | 0.7936    | 0.5587 | 0.6557 | 0.0057  |
+| 0.0165        | 0.63  | 20000 | 0.0161          | 0.9944   | 0.7949    | 0.5782 | 0.6694 | 0.0056  |
+| 0.0161        | 0.79  | 25000 | 0.0158          | 0.9945   | 0.7948    | 0.5830 | 0.6727 | 0.0055  |
+
+
+### Framework versions
+
+- Transformers 4.35.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.7.1
+- Tokenizers 0.14.1

all_results.json

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+    "epoch": 0.79,
+    "train_loss": 0.035478990478515625,
+    "train_runtime": 37421.8729,
+    "train_samples_per_second": 42.756,
+    "train_steps_per_second": 0.668
+}

config.json

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+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
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+}

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special_tokens_map.json

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tokenizer_config.json

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train_results.json

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training_args.bin

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