Instructions to use moos124/code-reasoning-0.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moos124/code-reasoning-0.5b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("moos124/code-reasoning-0.5b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 540, 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 70430032
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:090462ef8f606075af048f85b7e046b41976430da4f96c31f29d19d3c0d99f97
|
| 3 |
size 70430032
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 141058579
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7f080c3c3e9a8841d5f374bce88d1f132b493f39d9daa555483bb725580f05a3
|
| 3 |
size 141058579
|
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 sha256:5ba9e34cde3eeee92d5f00298627ddb43d984f163e0b84ea610723f9d6feda7e
|
| 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:bfcad7ace1953267f7e67920e5232af2f14d8f4d17fbdd7cef912bc890f95d17
|
| 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": 0.
|
| 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,
|
|
@@ -548,6 +548,16 @@
|
|
| 548 |
"mean_token_accuracy": 0.7418296962976456,
|
| 549 |
"num_tokens": 2445609.0,
|
| 550 |
"step": 530
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 551 |
}
|
| 552 |
],
|
| 553 |
"logging_steps": 10,
|
|
@@ -567,7 +577,7 @@
|
|
| 567 |
"attributes": {}
|
| 568 |
}
|
| 569 |
},
|
| 570 |
-
"total_flos": 1.
|
| 571 |
"train_batch_size": 4,
|
| 572 |
"trial_name": null,
|
| 573 |
"trial_params": null
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 0.1152,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 540,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 548 |
"mean_token_accuracy": 0.7418296962976456,
|
| 549 |
"num_tokens": 2445609.0,
|
| 550 |
"step": 530
|
| 551 |
+
},
|
| 552 |
+
{
|
| 553 |
+
"entropy": 1.037429604679346,
|
| 554 |
+
"epoch": 0.1152,
|
| 555 |
+
"grad_norm": 0.29860854148864746,
|
| 556 |
+
"learning_rate": 9.982899891076973e-05,
|
| 557 |
+
"loss": 1.1256014823913574,
|
| 558 |
+
"mean_token_accuracy": 0.7413557574152947,
|
| 559 |
+
"num_tokens": 2490595.0,
|
| 560 |
+
"step": 540
|
| 561 |
}
|
| 562 |
],
|
| 563 |
"logging_steps": 10,
|
|
|
|
| 577 |
"attributes": {}
|
| 578 |
}
|
| 579 |
},
|
| 580 |
+
"total_flos": 1.1864837044313088e+16,
|
| 581 |
"train_batch_size": 4,
|
| 582 |
"trial_name": null,
|
| 583 |
"trial_params": null
|