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Model: TarhanE/sft-count_loss-Qwen3-0.6B-mle0.5-ul0.5-tox0-e4
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Qwen/Qwen3-0.6B
+tags:
+- generated_from_trainer
+model-index:
+- name: sft-count_loss-Qwen3-0.6B-mle0.5-ul0.5-tox0-e4
+  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. -->
+
+# sft-count_loss-Qwen3-0.6B-mle0.5-ul0.5-tox0-e4
+
+This model is a fine-tuned version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.9505
+
+## 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: 3e-05
+- train_batch_size: 4
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 5
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.7934        | 0.2899 | 200  | 1.3768          |
+| 2.6787        | 0.5797 | 400  | 1.3584          |
+| 2.7074        | 0.8696 | 600  | 1.3443          |
+| 1.8508        | 1.1594 | 800  | 1.3934          |
+| 1.9016        | 1.4493 | 1000 | 1.4017          |
+| 1.8603        | 1.7391 | 1200 | 1.4073          |
+| 1.7469        | 2.0290 | 1400 | 1.6987          |
+| 0.9924        | 2.3188 | 1600 | 1.7187          |
+| 1.0118        | 2.6087 | 1800 | 1.7246          |
+| 0.9845        | 2.8986 | 2000 | 1.7222          |
+| 0.5651        | 3.1884 | 2200 | 1.9391          |
+| 0.5605        | 3.4783 | 2400 | 1.9573          |
+| 0.553         | 3.7681 | 2600 | 1.9505          |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1