metadata
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: >-
find_marker_both_sent_train_400_eval_40_random_permute_rerun_4_Qwen_Qwen1.5-4B_3e-4_lora
results: []
library_name: peft
find_marker_both_sent_train_400_eval_40_random_permute_rerun_4_Qwen_Qwen1.5-4B_3e-4_lora
This model is a fine-tuned version of Qwen/Qwen1.5-4B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3920
- Accuracy: 0.7643
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: 0.0003
- train_batch_size: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 50.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.6149 | 0.9968 | 117 | 1.2999 | 0.6755 |
0.862 | 1.9936 | 234 | 0.6614 | 0.7318 |
0.3519 | 2.9989 | 352 | 0.3529 | 0.7612 |
0.2097 | 3.9957 | 469 | 0.3055 | 0.7604 |
0.1746 | 4.9925 | 586 | 0.2799 | 0.7659 |
0.1507 | 5.9979 | 704 | 0.2721 | 0.7651 |
0.1431 | 6.9947 | 821 | 0.2592 | 0.7674 |
0.1381 | 8.0 | 939 | 0.2589 | 0.7667 |
0.1337 | 8.9968 | 1056 | 0.2509 | 0.7679 |
0.1292 | 9.9936 | 1173 | 0.2452 | 0.7682 |
0.1232 | 10.9989 | 1291 | 0.2604 | 0.7656 |
0.1214 | 11.9957 | 1408 | 0.2679 | 0.7653 |
0.119 | 12.9925 | 1525 | 0.2421 | 0.7681 |
0.1165 | 13.9979 | 1643 | 0.2545 | 0.7654 |
0.1161 | 14.9947 | 1760 | 0.2666 | 0.7630 |
0.1193 | 16.0 | 1878 | 0.2661 | 0.7645 |
0.1264 | 16.9968 | 1995 | 0.2994 | 0.7626 |
0.1201 | 17.9936 | 2112 | 0.2607 | 0.7647 |
0.1144 | 18.9989 | 2230 | 0.2665 | 0.7655 |
0.1147 | 19.9957 | 2347 | 0.2606 | 0.7646 |
0.1143 | 20.9925 | 2464 | 0.2834 | 0.7645 |
0.1105 | 21.9979 | 2582 | 0.2843 | 0.7645 |
0.1103 | 22.9947 | 2699 | 0.2959 | 0.7639 |
0.1081 | 24.0 | 2817 | 0.3331 | 0.7640 |
0.1093 | 24.9968 | 2934 | 0.3566 | 0.7640 |
0.1086 | 25.9936 | 3051 | 0.2995 | 0.7630 |
0.1124 | 26.9989 | 3169 | 0.2889 | 0.7624 |
0.1169 | 27.9957 | 3286 | 0.3392 | 0.7630 |
0.1225 | 28.9925 | 3403 | 0.2916 | 0.7633 |
0.1179 | 29.9979 | 3521 | 0.2572 | 0.7645 |
0.1139 | 30.9947 | 3638 | 0.3382 | 0.7635 |
0.1141 | 32.0 | 3756 | 0.3028 | 0.7635 |
0.1119 | 32.9968 | 3873 | 0.3388 | 0.7637 |
0.1124 | 33.9936 | 3990 | 0.3304 | 0.7636 |
0.1089 | 34.9989 | 4108 | 0.3556 | 0.7641 |
0.1095 | 35.9957 | 4225 | 0.3314 | 0.7641 |
0.1082 | 36.9925 | 4342 | 0.3770 | 0.7640 |
0.1071 | 37.9979 | 4460 | 0.3392 | 0.7645 |
0.1076 | 38.9947 | 4577 | 0.3363 | 0.7640 |
0.1074 | 40.0 | 4695 | 0.3731 | 0.7629 |
0.1289 | 40.9968 | 4812 | 0.3028 | 0.7634 |
0.1264 | 41.9936 | 4929 | 0.3093 | 0.7639 |
0.1126 | 42.9989 | 5047 | 0.3074 | 0.7643 |
0.1122 | 43.9957 | 5164 | 0.3375 | 0.7646 |
0.1096 | 44.9925 | 5281 | 0.3388 | 0.7645 |
0.1077 | 45.9979 | 5399 | 0.3173 | 0.7644 |
0.1063 | 46.9947 | 5516 | 0.3343 | 0.7643 |
0.1086 | 48.0 | 5634 | 0.3137 | 0.7644 |
0.1052 | 48.9968 | 5751 | 0.3941 | 0.7645 |
0.1078 | 49.8403 | 5850 | 0.3920 | 0.7643 |
Framework versions
- PEFT 0.5.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1