sophiayk/ST-trial-model

README.md

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+---
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: roberta-base-outputs
+  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. -->
+
+# roberta-base-outputs
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5836
+- Accuracy: 0.6636
+- F1: 0.6948
+- Precision: 0.6409
+- Recall: 0.7587
+
+## 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: 1e-06
+- train_batch_size: 8
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6984        | 0.1778 | 1000  | 0.6931          | 0.5072   | 0.4296 | 0.5167    | 0.3677 |
+| 0.6952        | 0.3556 | 2000  | 0.6932          | 0.4956   | 0.0032 | 0.6667    | 0.0016 |
+| 0.6931        | 0.5333 | 3000  | 0.6922          | 0.5314   | 0.3417 | 0.5874    | 0.2409 |
+| 0.6927        | 0.7111 | 4000  | 0.6901          | 0.5272   | 0.6625 | 0.5179    | 0.9192 |
+| 0.6883        | 0.8889 | 5000  | 0.6792          | 0.5714   | 0.6346 | 0.5570    | 0.7373 |
+| 0.6756        | 1.0667 | 6000  | 0.6521          | 0.6114   | 0.5702 | 0.6455    | 0.5107 |
+| 0.6476        | 1.2444 | 7000  | 0.6317          | 0.627    | 0.6909 | 0.5939    | 0.8257 |
+| 0.6278        | 1.4222 | 8000  | 0.6058          | 0.6474   | 0.6799 | 0.6276    | 0.7417 |
+| 0.6134        | 1.6    | 9000  | 0.5959          | 0.6564   | 0.6909 | 0.6328    | 0.7607 |
+| 0.6119        | 1.7778 | 10000 | 0.5870          | 0.6618   | 0.6933 | 0.6393    | 0.7571 |
+| 0.6033        | 1.9556 | 11000 | 0.5836          | 0.6636   | 0.6948 | 0.6409    | 0.7587 |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "roberta-base",
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.1",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

model.safetensors

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+size 498612824

training_args.bin

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