Instructions to use dschauhan08/MiniCPM5-1B-Checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dschauhan08/MiniCPM5-1B-Checkpoints with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dschauhan08/MiniCPM5-1B-Checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Training in progress, step 3696, 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 44871152
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:42c867da4435a602e7276ba7c21ae683ab39d13daad7fc0e5fd657358ebda620
|
| 3 |
size 44871152
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 23160933
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b9470208149ac9e2bfb288d43778f6d989ad837fe56f4630894d2046af831eed
|
| 3 |
size 23160933
|
last-checkpoint/scaler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1383
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:42d95b7b22877f7a7369647179abfb3ef136059915c0ffc1326249b0c778809b
|
| 3 |
size 1383
|
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:eb10833e49807d33253596a702add34258667ceb930380e040a68c918c50145e
|
| 3 |
size 1465
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -2,9 +2,9 @@
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
-
"epoch": 1.
|
| 6 |
"eval_steps": 500,
|
| 7 |
-
"global_step":
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
@@ -2535,6 +2535,62 @@
|
|
| 2535 |
"learning_rate": 3.367055234185191e-05,
|
| 2536 |
"loss": 0.41823325157165525,
|
| 2537 |
"step": 3610
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2538 |
}
|
| 2539 |
],
|
| 2540 |
"logging_steps": 10,
|
|
@@ -2554,7 +2610,7 @@
|
|
| 2554 |
"attributes": {}
|
| 2555 |
}
|
| 2556 |
},
|
| 2557 |
-
"total_flos": 6.
|
| 2558 |
"train_batch_size": 4,
|
| 2559 |
"trial_name": null,
|
| 2560 |
"trial_params": null
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 1.5135660898945429,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 3696,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 2535 |
"learning_rate": 3.367055234185191e-05,
|
| 2536 |
"loss": 0.41823325157165525,
|
| 2537 |
"step": 3610
|
| 2538 |
+
},
|
| 2539 |
+
{
|
| 2540 |
+
"epoch": 1.4824408723251765,
|
| 2541 |
+
"grad_norm": 0.15578892827033997,
|
| 2542 |
+
"learning_rate": 3.317570108031889e-05,
|
| 2543 |
+
"loss": 0.376281213760376,
|
| 2544 |
+
"step": 3620
|
| 2545 |
+
},
|
| 2546 |
+
{
|
| 2547 |
+
"epoch": 1.486536295689567,
|
| 2548 |
+
"grad_norm": 0.19605852663516998,
|
| 2549 |
+
"learning_rate": 3.268378899615621e-05,
|
| 2550 |
+
"loss": 0.36276628971099856,
|
| 2551 |
+
"step": 3630
|
| 2552 |
+
},
|
| 2553 |
+
{
|
| 2554 |
+
"epoch": 1.4906317190539573,
|
| 2555 |
+
"grad_norm": 0.22443526983261108,
|
| 2556 |
+
"learning_rate": 3.219483772545861e-05,
|
| 2557 |
+
"loss": 0.39970669746398924,
|
| 2558 |
+
"step": 3640
|
| 2559 |
+
},
|
| 2560 |
+
{
|
| 2561 |
+
"epoch": 1.4947271424183475,
|
| 2562 |
+
"grad_norm": 0.20385168492794037,
|
| 2563 |
+
"learning_rate": 3.1708868774093534e-05,
|
| 2564 |
+
"loss": 0.3872653007507324,
|
| 2565 |
+
"step": 3650
|
| 2566 |
+
},
|
| 2567 |
+
{
|
| 2568 |
+
"epoch": 1.4988225657827379,
|
| 2569 |
+
"grad_norm": 0.25204744935035706,
|
| 2570 |
+
"learning_rate": 3.1225903516754964e-05,
|
| 2571 |
+
"loss": 0.38168063163757326,
|
| 2572 |
+
"step": 3660
|
| 2573 |
+
},
|
| 2574 |
+
{
|
| 2575 |
+
"epoch": 1.502917989147128,
|
| 2576 |
+
"grad_norm": 0.2082594484090805,
|
| 2577 |
+
"learning_rate": 3.0745963196023555e-05,
|
| 2578 |
+
"loss": 0.3588885307312012,
|
| 2579 |
+
"step": 3670
|
| 2580 |
+
},
|
| 2581 |
+
{
|
| 2582 |
+
"epoch": 1.5070134125115184,
|
| 2583 |
+
"grad_norm": 0.21136775612831116,
|
| 2584 |
+
"learning_rate": 3.0269068921432032e-05,
|
| 2585 |
+
"loss": 0.39031205177307127,
|
| 2586 |
+
"step": 3680
|
| 2587 |
+
},
|
| 2588 |
+
{
|
| 2589 |
+
"epoch": 1.5111088358759086,
|
| 2590 |
+
"grad_norm": 0.18526561558246613,
|
| 2591 |
+
"learning_rate": 2.9795241668536977e-05,
|
| 2592 |
+
"loss": 0.40956802368164064,
|
| 2593 |
+
"step": 3690
|
| 2594 |
}
|
| 2595 |
],
|
| 2596 |
"logging_steps": 10,
|
|
|
|
| 2610 |
"attributes": {}
|
| 2611 |
}
|
| 2612 |
},
|
| 2613 |
+
"total_flos": 6.413772993948795e+17,
|
| 2614 |
"train_batch_size": 4,
|
| 2615 |
"trial_name": null,
|
| 2616 |
"trial_params": null
|