Model save

README.md

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+---
+base_model: Hartunka/tiny_bert_rand_100_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: tiny_bert_rand_100_v1_qqp
+  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. -->
+
+# tiny_bert_rand_100_v1_qqp
+
+This model is a fine-tuned version of [Hartunka/tiny_bert_rand_100_v1](https://huggingface.co/Hartunka/tiny_bert_rand_100_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5052
+- Accuracy: 0.8201
+- F1: 0.7678
+- Combined Score: 0.7939
+
+## 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: 256
+- eval_batch_size: 256
+- seed: 10
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.496         | 1.0   | 1422  | 0.4492          | 0.7838   | 0.6806 | 0.7322         |
+| 0.4089        | 2.0   | 2844  | 0.4196          | 0.8034   | 0.7191 | 0.7612         |
+| 0.3518        | 3.0   | 4266  | 0.4153          | 0.8110   | 0.7420 | 0.7765         |
+| 0.3062        | 4.0   | 5688  | 0.4296          | 0.8186   | 0.7423 | 0.7805         |
+| 0.2689        | 5.0   | 7110  | 0.4466          | 0.8198   | 0.7533 | 0.7866         |
+| 0.239         | 6.0   | 8532  | 0.4361          | 0.8202   | 0.7623 | 0.7912         |
+| 0.2131        | 7.0   | 9954  | 0.4664          | 0.8231   | 0.7650 | 0.7941         |
+| 0.1896        | 8.0   | 11376 | 0.5052          | 0.8201   | 0.7678 | 0.7939         |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.19.1

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