f2llm-sentiment-ablation-D
This model is a fine-tuned version of codefuse-ai/F2LLM-0.6B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0970
- F1 Macro: 0.4169
- F1 Weighted: 0.4924
- Accuracy: 0.4711
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Accuracy |
|---|---|---|---|---|---|---|
| 1.1566 | 1.0 | 222 | 1.1279 | 0.3285 | 0.3753 | 0.35 |
| 1.0448 | 2.0 | 444 | 1.0952 | 0.4131 | 0.5026 | 0.4908 |
| 1.0091 | 3.0 | 666 | 1.0941 | 0.4080 | 0.4725 | 0.45 |
| 0.9835 | 4.0 | 888 | 1.0984 | 0.4164 | 0.4881 | 0.4684 |
| 0.9328 | 5.0 | 1110 | 1.0970 | 0.4169 | 0.4924 | 0.4711 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.7.0
- Tokenizers 0.22.2
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