Classifier
Collection
5 items • Updated
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("TuringGame/Qwen3-0.6B-classifier")
model = AutoModelForSequenceClassification.from_pretrained("TuringGame/Qwen3-0.6B-classifier")Quick Links
Qwen3-0.6B-classifier
This model is a fine-tuned version of Qwen/Qwen3-0.6B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2290
- Accuracy: 0.9236
- F1: 0.8515
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0 | 0 | 0.7202 | 0.6830 | 0.2254 |
| No log | 0.2020 | 79 | 0.3226 | 0.8631 | 0.7293 |
| No log | 0.4041 | 158 | 0.2625 | 0.8948 | 0.7955 |
| No log | 0.6061 | 237 | 0.2433 | 0.9020 | 0.7964 |
| No log | 0.8082 | 316 | 0.2294 | 0.8919 | 0.7774 |
| No log | 1.0102 | 395 | 0.2312 | 0.9078 | 0.8232 |
| No log | 1.2123 | 474 | 0.3678 | 0.8905 | 0.8 |
| 0.3067 | 1.4143 | 553 | 0.2314 | 0.9164 | 0.8362 |
| 0.3067 | 1.6164 | 632 | 0.2346 | 0.9207 | 0.8415 |
| 0.3067 | 1.8184 | 711 | 0.2290 | 0.9236 | 0.8515 |
Framework versions
- Transformers 4.53.3
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.2
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TuringGame/Qwen3-0.6B-classifier")