Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: twitter-roberta-base-sentiment
+  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. -->
+
+# twitter-roberta-base-sentiment
+
+This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9462
+- Accuracy: 0.7222
+- Macro Precision: 0.7068
+- Macro Recall: 0.7491
+- Macro F1: 0.7246
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Macro Precision | Macro Recall | Macro F1 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|
+| 0.9337        | 0.2667 | 1000 | 0.8398          | 0.6273   | 0.6577          | 0.6723       | 0.6322   |
+| 0.8101        | 0.5333 | 2000 | 0.7526          | 0.6780   | 0.6598          | 0.7406       | 0.6851   |
+| 0.7097        | 0.8    | 3000 | 0.8075          | 0.7068   | 0.6853          | 0.7515       | 0.7081   |
+| 0.5513        | 1.0667 | 4000 | 0.8310          | 0.7113   | 0.7007          | 0.7316       | 0.7135   |
+| 0.4368        | 1.3333 | 5000 | 0.9000          | 0.7154   | 0.7001          | 0.7487       | 0.7192   |
+| 0.4084        | 1.6    | 6000 | 0.9042          | 0.7154   | 0.7035          | 0.7413       | 0.7194   |
+| 0.3481        | 1.8667 | 7000 | 0.9868          | 0.7246   | 0.7121          | 0.7441       | 0.7255   |
+| 0.3693        | 2.0    | 7500 | 0.9462          | 0.7222   | 0.7068          | 0.7491       | 0.7246   |
+
+
+### Framework versions
+
+- Transformers 5.9.0
+- Pytorch 2.11.0+cu128
+- Datasets 4.8.5
+- Tokenizers 0.22.2

runs/May26_13-20-08_MSI/events.out.tfevents.1779816008.MSI

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+size 12020

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "is_local": false,
+  "local_files_only": false,
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}