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 870, 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:ddb73b24f7c24360f86d65b2aae05a3ca8d784fd150ca6942d5aa861f92a3940
|
| 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 sha256:036591dbbb25389e3e01d287cccfbe6918a85cccfcf7c4483d9a8e91c3447de5
|
| 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:bd521810c87442802b38d9ddb25a7dac561287aff02c46dc14fcbc8a24272fb9
|
| 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:addf757fbcba66917f74ece6118fc7351d4fc2adf0697c9d475ff88757237430
|
| 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,
|
|
@@ -878,6 +878,16 @@
|
|
| 878 |
"mean_token_accuracy": 0.7761695921421051,
|
| 879 |
"num_tokens": 3991940.0,
|
| 880 |
"step": 860
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 881 |
}
|
| 882 |
],
|
| 883 |
"logging_steps": 10,
|
|
@@ -897,7 +907,7 @@
|
|
| 897 |
"attributes": {}
|
| 898 |
}
|
| 899 |
},
|
| 900 |
-
"total_flos": 1.
|
| 901 |
"train_batch_size": 4,
|
| 902 |
"trial_name": null,
|
| 903 |
"trial_params": null
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 0.1856,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 870,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 878 |
"mean_token_accuracy": 0.7761695921421051,
|
| 879 |
"num_tokens": 3991940.0,
|
| 880 |
"step": 860
|
| 881 |
+
},
|
| 882 |
+
{
|
| 883 |
+
"entropy": 1.1529859654605388,
|
| 884 |
+
"epoch": 0.1856,
|
| 885 |
+
"grad_norm": 0.26249563694000244,
|
| 886 |
+
"learning_rate": 9.903334622517643e-05,
|
| 887 |
+
"loss": 1.2724492073059082,
|
| 888 |
+
"mean_token_accuracy": 0.7244490720331669,
|
| 889 |
+
"num_tokens": 4050343.0,
|
| 890 |
+
"step": 870
|
| 891 |
}
|
| 892 |
],
|
| 893 |
"logging_steps": 10,
|
|
|
|
| 907 |
"attributes": {}
|
| 908 |
}
|
| 909 |
},
|
| 910 |
+
"total_flos": 1.9197380036760576e+16,
|
| 911 |
"train_batch_size": 4,
|
| 912 |
"trial_name": null,
|
| 913 |
"trial_params": null
|