Instructions to use kon171verma/intent-classifier-experiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kon171verma/intent-classifier-experiments with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Konark Verma commited on
Add DoRA+ training report: qwen3-0.6b_C_1k [20260826_153242]
Browse files
reports/v2.0/doraplus/reports_training/qwen3-0.6b_C_1k_20260826_153242.json
ADDED
|
@@ -0,0 +1,140 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"model_key": "qwen3-0.6b",
|
| 3 |
+
"model_id": "Qwen/Qwen3-0.6B",
|
| 4 |
+
"lora_config": "C",
|
| 5 |
+
"lora_config_desc": "Wide — full attention + MLP, rank 16",
|
| 6 |
+
"dataset_size": "1k",
|
| 7 |
+
"technique": "DoRA+",
|
| 8 |
+
"device": "cuda",
|
| 9 |
+
"dtype": "bfloat16",
|
| 10 |
+
"timestamp": "20260826_153242",
|
| 11 |
+
"prompt_format": "tool_id_v1",
|
| 12 |
+
"tool_id_scheme": "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ",
|
| 13 |
+
"no_tool_id": "-",
|
| 14 |
+
"gradient_checkpointing": true,
|
| 15 |
+
"trainable_params": 10436608,
|
| 16 |
+
"total_params": 606486528,
|
| 17 |
+
"trainable_pct": 1.7208,
|
| 18 |
+
"steps_per_epoch": 50,
|
| 19 |
+
"total_steps_trained": 200,
|
| 20 |
+
"early_stopped": false,
|
| 21 |
+
"early_stopping_patience": 2,
|
| 22 |
+
"early_stopping_threshold": 0.001,
|
| 23 |
+
"peak_memory_mb": 2949.4,
|
| 24 |
+
"total_training_time_s": 1428.5,
|
| 25 |
+
"final_train_loss": 0.105573,
|
| 26 |
+
"final_eval_loss": 0.225153,
|
| 27 |
+
"final_val_accuracy": 0.89,
|
| 28 |
+
"final_train_accuracy": 0.96,
|
| 29 |
+
"hf_repo": "kon172verma/intent-classifier-experiments",
|
| 30 |
+
"hf_subfolder": "v2.0/qwen3-0.6b_DoRA+_C_1k_20260826-153232",
|
| 31 |
+
"version": "v2.0",
|
| 32 |
+
"log_history": [
|
| 33 |
+
{
|
| 34 |
+
"loss": 0.2916320991516113,
|
| 35 |
+
"grad_norm": 2.743527412414551,
|
| 36 |
+
"learning_rate": 5.577423184847932e-05,
|
| 37 |
+
"entropy": 0.1707103259768337,
|
| 38 |
+
"num_tokens": 304665.0,
|
| 39 |
+
"mean_token_accuracy": 0.9470833283662796,
|
| 40 |
+
"epoch": 1.0,
|
| 41 |
+
"step": 50
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"eval_loss": 0.09938085824251175,
|
| 45 |
+
"eval_model_preparation_time": 0.0207,
|
| 46 |
+
"eval_runtime": 8.7257,
|
| 47 |
+
"eval_samples_per_second": 11.46,
|
| 48 |
+
"eval_steps_per_second": 1.49,
|
| 49 |
+
"eval_entropy": 0.08493176102638245,
|
| 50 |
+
"eval_num_tokens": 304665.0,
|
| 51 |
+
"eval_mean_token_accuracy": 0.9711538461538461,
|
| 52 |
+
"epoch": 1.0,
|
| 53 |
+
"step": 50,
|
| 54 |
+
"train_accuracy": 0.94,
|
| 55 |
+
"eval_accuracy": 0.92
|
| 56 |
+
},
|
| 57 |
+
{
|
| 58 |
+
"loss": 0.03447272777557373,
|
| 59 |
+
"grad_norm": 0.003604077035561204,
|
| 60 |
+
"learning_rate": 2.7337132953697554e-08,
|
| 61 |
+
"entropy": 0.01031205168867018,
|
| 62 |
+
"num_tokens": 609330.0,
|
| 63 |
+
"mean_token_accuracy": 0.9924999976158142,
|
| 64 |
+
"epoch": 2.0,
|
| 65 |
+
"step": 100
|
| 66 |
+
},
|
| 67 |
+
{
|
| 68 |
+
"eval_loss": 0.06900880485773087,
|
| 69 |
+
"eval_model_preparation_time": 0.0207,
|
| 70 |
+
"eval_runtime": 8.7269,
|
| 71 |
+
"eval_samples_per_second": 11.459,
|
| 72 |
+
"eval_steps_per_second": 1.49,
|
| 73 |
+
"eval_entropy": 0.004303412762685464,
|
| 74 |
+
"eval_num_tokens": 609330.0,
|
| 75 |
+
"eval_mean_token_accuracy": 0.9903846107996427,
|
| 76 |
+
"epoch": 2.0,
|
| 77 |
+
"step": 100,
|
| 78 |
+
"train_accuracy": 0.98,
|
| 79 |
+
"eval_accuracy": 0.97
|
| 80 |
+
},
|
| 81 |
+
{
|
| 82 |
+
"loss": 0.004043597877025604,
|
| 83 |
+
"grad_norm": 2.7254981994628906,
|
| 84 |
+
"learning_rate": 5.247918773366112e-05,
|
| 85 |
+
"entropy": 0.0042462384887039665,
|
| 86 |
+
"num_tokens": 913995.0,
|
| 87 |
+
"mean_token_accuracy": 0.9987499994039536,
|
| 88 |
+
"epoch": 3.0,
|
| 89 |
+
"step": 150
|
| 90 |
+
},
|
| 91 |
+
{
|
| 92 |
+
"eval_loss": 0.13582678139209747,
|
| 93 |
+
"eval_model_preparation_time": 0.0207,
|
| 94 |
+
"eval_runtime": 8.7306,
|
| 95 |
+
"eval_samples_per_second": 11.454,
|
| 96 |
+
"eval_steps_per_second": 1.489,
|
| 97 |
+
"eval_entropy": 0.006184923578985035,
|
| 98 |
+
"eval_num_tokens": 913995.0,
|
| 99 |
+
"eval_mean_token_accuracy": 0.9807692261842581,
|
| 100 |
+
"epoch": 3.0,
|
| 101 |
+
"step": 150,
|
| 102 |
+
"train_accuracy": 0.98,
|
| 103 |
+
"eval_accuracy": 0.95
|
| 104 |
+
},
|
| 105 |
+
{
|
| 106 |
+
"loss": 0.0921437931060791,
|
| 107 |
+
"grad_norm": 3.1604411602020264,
|
| 108 |
+
"learning_rate": 9.956320346634876e-05,
|
| 109 |
+
"entropy": 0.03684742745448602,
|
| 110 |
+
"num_tokens": 1218660.0,
|
| 111 |
+
"mean_token_accuracy": 0.9858333307504654,
|
| 112 |
+
"epoch": 4.0,
|
| 113 |
+
"step": 200
|
| 114 |
+
},
|
| 115 |
+
{
|
| 116 |
+
"eval_loss": 0.22515279054641724,
|
| 117 |
+
"eval_model_preparation_time": 0.0207,
|
| 118 |
+
"eval_runtime": 8.7218,
|
| 119 |
+
"eval_samples_per_second": 11.465,
|
| 120 |
+
"eval_steps_per_second": 1.491,
|
| 121 |
+
"eval_entropy": 0.02783593273936556,
|
| 122 |
+
"eval_num_tokens": 1218660.0,
|
| 123 |
+
"eval_mean_token_accuracy": 0.9615384615384616,
|
| 124 |
+
"epoch": 4.0,
|
| 125 |
+
"step": 200,
|
| 126 |
+
"train_accuracy": 0.96,
|
| 127 |
+
"eval_accuracy": 0.89
|
| 128 |
+
},
|
| 129 |
+
{
|
| 130 |
+
"train_runtime": 1428.0695,
|
| 131 |
+
"train_samples_per_second": 2.241,
|
| 132 |
+
"train_steps_per_second": 0.14,
|
| 133 |
+
"total_flos": 5433422829060096.0,
|
| 134 |
+
"train_loss": 0.10557305447757244,
|
| 135 |
+
"epoch": 4.0,
|
| 136 |
+
"step": 200
|
| 137 |
+
}
|
| 138 |
+
],
|
| 139 |
+
"hf_report_path": "reports/v2.0/doraplus/reports_training/qwen3-0.6b_C_1k_20260826_153242.json"
|
| 140 |
+
}
|