Instructions to use C3DS/FLICC-Qwen3.5-9B-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use C3DS/FLICC-Qwen3.5-9B-lora with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("C3DS/FLICC-Qwen3.5-9B-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Training in progress, step 250, checkpoint
Browse files
last-checkpoint/adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 116429720
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e83ecce4172b6569813c03ab52f2be1fa55ab1932d6bca2b0745ba565927325f
|
| 3 |
size 116429720
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 59409573
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:59de098eb21d287d0ff5d641369521b22a7a7a5a4a5700d53a5b4c0fca9d5990
|
| 3 |
size 59409573
|
last-checkpoint/rng_state.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 14645
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1255b82ec9f462fef6f8c2f4a8ee876c4b6d998a53c99546a4eddcc1aabaefc7
|
| 3 |
size 14645
|
last-checkpoint/scheduler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1465
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:810175fa292ba2b217f4f86dac014c190963d55e5a29863cf85601d5d54b1bc7
|
| 3 |
size 1465
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -1,10 +1,10 @@
|
|
| 1 |
{
|
| 2 |
-
"best_global_step":
|
| 3 |
-
"best_metric": 0.
|
| 4 |
-
"best_model_checkpoint": "FLICC-Qwen3.5-9B/checkpoint-
|
| 5 |
-
"epoch":
|
| 6 |
"eval_steps": 25,
|
| 7 |
-
"global_step":
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
@@ -352,6 +352,92 @@
|
|
| 352 |
"eval_samples_per_second": 8.814,
|
| 353 |
"eval_steps_per_second": 2.241,
|
| 354 |
"step": 200
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 355 |
}
|
| 356 |
],
|
| 357 |
"logging_steps": 5,
|
|
@@ -371,7 +457,7 @@
|
|
| 371 |
"attributes": {}
|
| 372 |
}
|
| 373 |
},
|
| 374 |
-
"total_flos": 1.
|
| 375 |
"train_batch_size": 1,
|
| 376 |
"trial_name": null,
|
| 377 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
+
"best_global_step": 250,
|
| 3 |
+
"best_metric": 0.14815586805343628,
|
| 4 |
+
"best_model_checkpoint": "FLICC-Qwen3.5-9B/checkpoint-250",
|
| 5 |
+
"epoch": 1.2379182156133828,
|
| 6 |
"eval_steps": 25,
|
| 7 |
+
"global_step": 250,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 352 |
"eval_samples_per_second": 8.814,
|
| 353 |
"eval_steps_per_second": 2.241,
|
| 354 |
"step": 200
|
| 355 |
+
},
|
| 356 |
+
{
|
| 357 |
+
"epoch": 1.0148698884758365,
|
| 358 |
+
"grad_norm": 0.07653596252202988,
|
| 359 |
+
"learning_rate": 0.00015211495991996027,
|
| 360 |
+
"loss": 0.16517894268035888,
|
| 361 |
+
"step": 205
|
| 362 |
+
},
|
| 363 |
+
{
|
| 364 |
+
"epoch": 1.0396530359355638,
|
| 365 |
+
"grad_norm": 0.07493323087692261,
|
| 366 |
+
"learning_rate": 0.00014984775852212807,
|
| 367 |
+
"loss": 0.14664943218231202,
|
| 368 |
+
"step": 210
|
| 369 |
+
},
|
| 370 |
+
{
|
| 371 |
+
"epoch": 1.0644361833952911,
|
| 372 |
+
"grad_norm": 0.07914339751005173,
|
| 373 |
+
"learning_rate": 0.00014754593388242117,
|
| 374 |
+
"loss": 0.14977338314056396,
|
| 375 |
+
"step": 215
|
| 376 |
+
},
|
| 377 |
+
{
|
| 378 |
+
"epoch": 1.0892193308550187,
|
| 379 |
+
"grad_norm": 0.09382504969835281,
|
| 380 |
+
"learning_rate": 0.00014521108480154032,
|
| 381 |
+
"loss": 0.14892799854278566,
|
| 382 |
+
"step": 220
|
| 383 |
+
},
|
| 384 |
+
{
|
| 385 |
+
"epoch": 1.114002478314746,
|
| 386 |
+
"grad_norm": 0.08522579073905945,
|
| 387 |
+
"learning_rate": 0.0001428448330182931,
|
| 388 |
+
"loss": 0.13943066596984863,
|
| 389 |
+
"step": 225
|
| 390 |
+
},
|
| 391 |
+
{
|
| 392 |
+
"epoch": 1.114002478314746,
|
| 393 |
+
"eval_loss": 0.1489669382572174,
|
| 394 |
+
"eval_runtime": 20.0756,
|
| 395 |
+
"eval_samples_per_second": 8.817,
|
| 396 |
+
"eval_steps_per_second": 2.242,
|
| 397 |
+
"step": 225
|
| 398 |
+
},
|
| 399 |
+
{
|
| 400 |
+
"epoch": 1.1387856257744733,
|
| 401 |
+
"grad_norm": 0.10055539757013321,
|
| 402 |
+
"learning_rate": 0.00014044882208316713,
|
| 403 |
+
"loss": 0.15772825479507446,
|
| 404 |
+
"step": 230
|
| 405 |
+
},
|
| 406 |
+
{
|
| 407 |
+
"epoch": 1.1635687732342008,
|
| 408 |
+
"grad_norm": 0.08639902621507645,
|
| 409 |
+
"learning_rate": 0.00013802471621675338,
|
| 410 |
+
"loss": 0.13583142757415773,
|
| 411 |
+
"step": 235
|
| 412 |
+
},
|
| 413 |
+
{
|
| 414 |
+
"epoch": 1.1883519206939281,
|
| 415 |
+
"grad_norm": 0.0846349224448204,
|
| 416 |
+
"learning_rate": 0.000135574199153812,
|
| 417 |
+
"loss": 0.13156899213790893,
|
| 418 |
+
"step": 240
|
| 419 |
+
},
|
| 420 |
+
{
|
| 421 |
+
"epoch": 1.2131350681536555,
|
| 422 |
+
"grad_norm": 0.08887381851673126,
|
| 423 |
+
"learning_rate": 0.00013309897297378455,
|
| 424 |
+
"loss": 0.14310439825057983,
|
| 425 |
+
"step": 245
|
| 426 |
+
},
|
| 427 |
+
{
|
| 428 |
+
"epoch": 1.2379182156133828,
|
| 429 |
+
"grad_norm": 0.08967562019824982,
|
| 430 |
+
"learning_rate": 0.00013060075691856407,
|
| 431 |
+
"loss": 0.15425143241882325,
|
| 432 |
+
"step": 250
|
| 433 |
+
},
|
| 434 |
+
{
|
| 435 |
+
"epoch": 1.2379182156133828,
|
| 436 |
+
"eval_loss": 0.14815586805343628,
|
| 437 |
+
"eval_runtime": 20.0845,
|
| 438 |
+
"eval_samples_per_second": 8.813,
|
| 439 |
+
"eval_steps_per_second": 2.241,
|
| 440 |
+
"step": 250
|
| 441 |
}
|
| 442 |
],
|
| 443 |
"logging_steps": 5,
|
|
|
|
| 457 |
"attributes": {}
|
| 458 |
}
|
| 459 |
},
|
| 460 |
+
"total_flos": 1.707753437024616e+17,
|
| 461 |
"train_batch_size": 1,
|
| 462 |
"trial_name": null,
|
| 463 |
"trial_params": null
|