fleet-sft-full
This model is a fine-tuned version of Qwen/Qwen3-32B on the fleet_trajectories_train dataset. It achieves the following results on the evaluation set:
- Loss: 1.8278
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_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_ratio: 0.05
- num_epochs: 50.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0 | 0 | 1.4682 |
| 1.3518 | 0.7143 | 5 | 1.3431 |
| 0.9051 | 1.4286 | 10 | 1.2059 |
| 0.8625 | 2.1429 | 15 | 1.1277 |
| 0.6971 | 2.8571 | 20 | 1.1145 |
| 0.4243 | 3.5714 | 25 | 1.1612 |
| 0.1901 | 4.2857 | 30 | 1.3399 |
| 0.1171 | 5.0 | 35 | 1.3959 |
| 0.0593 | 5.7143 | 40 | 1.4992 |
| 0.0265 | 6.4286 | 45 | 1.5967 |
| 0.0229 | 7.1429 | 50 | 1.6269 |
| 0.0167 | 7.8571 | 55 | 1.6505 |
| 0.0119 | 8.5714 | 60 | 1.6626 |
| 0.0094 | 9.2857 | 65 | 1.6874 |
| 0.0089 | 10.0 | 70 | 1.7035 |
| 0.0062 | 10.7143 | 75 | 1.7053 |
| 0.0072 | 11.4286 | 80 | 1.7082 |
| 0.008 | 12.1429 | 85 | 1.6972 |
| 0.006 | 12.8571 | 90 | 1.6969 |
| 0.0044 | 13.5714 | 95 | 1.7049 |
| 0.0036 | 14.2857 | 100 | 1.7229 |
| 0.0035 | 15.0 | 105 | 1.7421 |
| 0.0026 | 15.7143 | 110 | 1.7550 |
| 0.0023 | 16.4286 | 115 | 1.7617 |
| 0.0021 | 17.1429 | 120 | 1.7656 |
| 0.0025 | 17.8571 | 125 | 1.7683 |
| 0.0018 | 18.5714 | 130 | 1.7750 |
| 0.002 | 19.2857 | 135 | 1.7667 |
| 0.0036 | 20.0 | 140 | 1.7492 |
| 0.0025 | 20.7143 | 145 | 1.7378 |
| 0.0017 | 21.4286 | 150 | 1.7389 |
| 0.0016 | 22.1429 | 155 | 1.7510 |
| 0.0016 | 22.8571 | 160 | 1.7623 |
| 0.0014 | 23.5714 | 165 | 1.7705 |
| 0.0013 | 24.2857 | 170 | 1.7751 |
| 0.0015 | 25.0 | 175 | 1.7802 |
| 0.0011 | 25.7143 | 180 | 1.7830 |
| 0.0012 | 26.4286 | 185 | 1.7873 |
| 0.0011 | 27.1429 | 190 | 1.7919 |
| 0.0012 | 27.8571 | 195 | 1.7959 |
| 0.0012 | 28.5714 | 200 | 1.7993 |
| 0.001 | 29.2857 | 205 | 1.8018 |
| 0.0012 | 30.0 | 210 | 1.8040 |
| 0.001 | 30.7143 | 215 | 1.8073 |
| 0.001 | 31.4286 | 220 | 1.8092 |
| 0.0014 | 32.1429 | 225 | 1.8116 |
| 0.0011 | 32.8571 | 230 | 1.8135 |
| 0.001 | 33.5714 | 235 | 1.8141 |
| 0.0011 | 34.2857 | 240 | 1.8167 |
| 0.0009 | 35.0 | 245 | 1.8182 |
| 0.001 | 35.7143 | 250 | 1.8190 |
| 0.0011 | 36.4286 | 255 | 1.8204 |
| 0.0012 | 37.1429 | 260 | 1.8216 |
| 0.0009 | 37.8571 | 265 | 1.8221 |
| 0.001 | 38.5714 | 270 | 1.8223 |
| 0.0013 | 39.2857 | 275 | 1.8238 |
| 0.0011 | 40.0 | 280 | 1.8247 |
| 0.0009 | 40.7143 | 285 | 1.8251 |
| 0.0011 | 41.4286 | 290 | 1.8253 |
| 0.001 | 42.1429 | 295 | 1.8262 |
| 0.001 | 42.8571 | 300 | 1.8267 |
| 0.0011 | 43.5714 | 305 | 1.8267 |
| 0.0012 | 44.2857 | 310 | 1.8272 |
| 0.0009 | 45.0 | 315 | 1.8278 |
| 0.0008 | 45.7143 | 320 | 1.8276 |
| 0.0009 | 46.4286 | 325 | 1.8282 |
| 0.001 | 47.1429 | 330 | 1.8282 |
| 0.001 | 47.8571 | 335 | 1.8279 |
| 0.0008 | 48.5714 | 340 | 1.8282 |
| 0.0012 | 49.2857 | 345 | 1.8281 |
| 0.001 | 50.0 | 350 | 1.8278 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
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