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 4110, 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:ea9e00f753bb1bbcfb5a5ddb4fd2666ab8f228d9591da3a11c6541456f9fdf45
|
| 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 sha256:2d123a674a35d67ad00943ce1141096bd35bf0ab734b4de43d14e05f5eebc904
|
| 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 sha256:2d010fa2a336c827a39930a13e22ca671772759564efcec24e06726aba01e59d
|
| 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:ae0ef84f22e1a51f0501bdb9dd2984ff5a4709a4014a3b5bf10482092bf9db69
|
| 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,
|
|
@@ -4118,6 +4118,16 @@
|
|
| 4118 |
"mean_token_accuracy": 0.7781016409397126,
|
| 4119 |
"num_tokens": 19112840.0,
|
| 4120 |
"step": 4100
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4121 |
}
|
| 4122 |
],
|
| 4123 |
"logging_steps": 10,
|
|
@@ -4137,7 +4147,7 @@
|
|
| 4137 |
"attributes": {}
|
| 4138 |
}
|
| 4139 |
},
|
| 4140 |
-
"total_flos": 9.
|
| 4141 |
"train_batch_size": 4,
|
| 4142 |
"trial_name": null,
|
| 4143 |
"trial_params": null
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 0.8768,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 4110,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 4118 |
"mean_token_accuracy": 0.7781016409397126,
|
| 4119 |
"num_tokens": 19112840.0,
|
| 4120 |
"step": 4100
|
| 4121 |
+
},
|
| 4122 |
+
{
|
| 4123 |
+
"entropy": 0.8111571930348873,
|
| 4124 |
+
"epoch": 0.8768,
|
| 4125 |
+
"grad_norm": 0.24323873221874237,
|
| 4126 |
+
"learning_rate": 6.248343714855884e-05,
|
| 4127 |
+
"loss": 0.8503658294677734,
|
| 4128 |
+
"mean_token_accuracy": 0.7953767567873001,
|
| 4129 |
+
"num_tokens": 19155980.0,
|
| 4130 |
+
"step": 4110
|
| 4131 |
}
|
| 4132 |
],
|
| 4133 |
"logging_steps": 10,
|
|
|
|
| 4147 |
"attributes": {}
|
| 4148 |
}
|
| 4149 |
},
|
| 4150 |
+
"total_flos": 9.064289810878157e+16,
|
| 4151 |
"train_batch_size": 4,
|
| 4152 |
"trial_name": null,
|
| 4153 |
"trial_params": null
|