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 3830, 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 sha256:47d69eacbb2f7117566a906f72be964ad8232e118d260c4d4f6dc65268da53b8
|
| 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 sha256:4cf16fcd679e2b6a523452aa551fa8ac67e2743efa5e80eee82568d9fa0b8782
|
| 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:cb6feb2759bca0e327b4d2bf4dac4280a1cdd2e253d40ea6c3d1d38efff607ab
|
| 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 sha256:492633a0e689414f8b596d271b8f83db32739ab33c218ebbb5fa0743993f69de
|
| 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,
|
|
@@ -3838,6 +3838,16 @@
|
|
| 3838 |
"mean_token_accuracy": 0.7579805940389633,
|
| 3839 |
"num_tokens": 17796312.0,
|
| 3840 |
"step": 3820
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3841 |
}
|
| 3842 |
],
|
| 3843 |
"logging_steps": 10,
|
|
@@ -3857,7 +3867,7 @@
|
|
| 3857 |
"attributes": {}
|
| 3858 |
}
|
| 3859 |
},
|
| 3860 |
-
"total_flos": 8.
|
| 3861 |
"train_batch_size": 4,
|
| 3862 |
"trial_name": null,
|
| 3863 |
"trial_params": null
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 0.8170666666666667,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 3830,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 3838 |
"mean_token_accuracy": 0.7579805940389633,
|
| 3839 |
"num_tokens": 17796312.0,
|
| 3840 |
"step": 3820
|
| 3841 |
+
},
|
| 3842 |
+
{
|
| 3843 |
+
"entropy": 1.0881080597639083,
|
| 3844 |
+
"epoch": 0.8170666666666667,
|
| 3845 |
+
"grad_norm": 0.2615782618522644,
|
| 3846 |
+
"learning_rate": 6.711004206939491e-05,
|
| 3847 |
+
"loss": 1.20444917678833,
|
| 3848 |
+
"mean_token_accuracy": 0.7393553704023361,
|
| 3849 |
+
"num_tokens": 17849058.0,
|
| 3850 |
+
"step": 3830
|
| 3851 |
}
|
| 3852 |
],
|
| 3853 |
"logging_steps": 10,
|
|
|
|
| 3867 |
"attributes": {}
|
| 3868 |
}
|
| 3869 |
},
|
| 3870 |
+
"total_flos": 8.453106679916851e+16,
|
| 3871 |
"train_batch_size": 4,
|
| 3872 |
"trial_name": null,
|
| 3873 |
"trial_params": null
|