Model save

README.md

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+---
+base_model: Hartunka/tiny_bert_rand_100_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: tiny_bert_rand_100_v1_mnli
+  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_mnli
+
+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: 0.9937
+- Accuracy: 0.6231
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.9939        | 1.0   | 1534  | 0.9340          | 0.5477   |
+| 0.9106        | 2.0   | 3068  | 0.8888          | 0.5792   |
+| 0.8576        | 3.0   | 4602  | 0.8594          | 0.6055   |
+| 0.8116        | 4.0   | 6136  | 0.8516          | 0.6134   |
+| 0.7679        | 5.0   | 7670  | 0.8467          | 0.6204   |
+| 0.7263        | 6.0   | 9204  | 0.8595          | 0.6275   |
+| 0.6861        | 7.0   | 10738 | 0.8681          | 0.6259   |
+| 0.6464        | 8.0   | 12272 | 0.9058          | 0.6231   |
+| 0.6076        | 9.0   | 13806 | 0.9309          | 0.6247   |
+| 0.5699        | 10.0  | 15340 | 0.9937          | 0.6231   |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.19.1

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