End of training

README.md

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+---
+base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: twitter-roberta-base-sentiment-latest
+  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-latest
+
+This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3302
+- Accuracy: 0.784
+
+## 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-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 600
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.8113        | 0.12  | 30   | 0.7971          | 0.418    |
+| 0.6733        | 0.24  | 60   | 0.6551          | 0.469    |
+| 0.5712        | 0.36  | 90   | 0.5713          | 0.522    |
+| 0.5234        | 0.48  | 120  | 0.5311          | 0.565    |
+| 0.5406        | 0.6   | 150  | 0.4938          | 0.6595   |
+| 0.4856        | 0.72  | 180  | 0.4482          | 0.692    |
+| 0.4732        | 0.84  | 210  | 0.4147          | 0.7185   |
+| 0.4217        | 0.96  | 240  | 0.4038          | 0.726    |
+| 0.4097        | 1.08  | 270  | 0.3828          | 0.7375   |
+| 0.3911        | 1.2   | 300  | 0.3928          | 0.735    |
+| 0.3779        | 1.32  | 330  | 0.3767          | 0.7555   |
+| 0.3829        | 1.44  | 360  | 0.3705          | 0.74     |
+| 0.3596        | 1.56  | 390  | 0.3905          | 0.744    |
+| 0.3626        | 1.68  | 420  | 0.3712          | 0.7425   |
+| 0.3763        | 1.8   | 450  | 0.3679          | 0.752    |
+| 0.3722        | 1.92  | 480  | 0.3353          | 0.7805   |
+| 0.3387        | 2.04  | 510  | 0.3504          | 0.768    |
+| 0.3247        | 2.16  | 540  | 0.3573          | 0.766    |
+| 0.3242        | 2.28  | 570  | 0.3526          | 0.7775   |
+| 0.4003        | 2.4   | 600  | 0.3413          | 0.7785   |
+| 0.352         | 2.52  | 630  | 0.3547          | 0.763    |
+| 0.3521        | 2.64  | 660  | 0.3449          | 0.7835   |
+| 0.29          | 2.76  | 690  | 0.3270          | 0.7875   |
+| 0.3017        | 2.88  | 720  | 0.3302          | 0.784    |
+| 0.3086        | 3.0   | 750  | 0.3401          | 0.782    |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

pytorch_model.bin

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