Instructions to use tuanna08go/a45bc180-e906-4fa6-b3ca-f6bb98da93fb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tuanna08go/a45bc180-e906-4fa6-b3ca-f6bb98da93fb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Hermes-2-Pro-Mistral-7B") model = PeftModel.from_pretrained(base_model, "tuanna08go/a45bc180-e906-4fa6-b3ca-f6bb98da93fb") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 39, 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 83945296
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:19283cf2f5f8b60a4c09f96d8975b3ad32892d54420ed89028ee06da9debe909
|
| 3 |
size 83945296
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 43122580
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:07d81e57f8498eddd6e252b5780aa49c5d49057ea1fe6dd11ef55468c8a00dd8
|
| 3 |
size 43122580
|
last-checkpoint/rng_state.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 14244
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:89be65360c462d9c4812bfee4e603b36894408ac274af51796d35fb242819f3e
|
| 3 |
size 14244
|
last-checkpoint/scheduler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1064
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0c50dbaa792cda4a28fbbc2acb2a3e03c59530712bbc5107212d33064d193da4
|
| 3 |
size 1064
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -1,9 +1,9 @@
|
|
| 1 |
{
|
| 2 |
"best_metric": null,
|
| 3 |
"best_model_checkpoint": null,
|
| 4 |
-
"epoch": 0.
|
| 5 |
"eval_steps": 10,
|
| 6 |
-
"global_step":
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
@@ -66,6 +66,28 @@
|
|
| 66 |
"learning_rate": 6.91341716182545e-05,
|
| 67 |
"loss": 5.618,
|
| 68 |
"step": 25
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 69 |
}
|
| 70 |
],
|
| 71 |
"logging_steps": 5,
|
|
@@ -85,7 +107,7 @@
|
|
| 85 |
"attributes": {}
|
| 86 |
}
|
| 87 |
},
|
| 88 |
-
"total_flos":
|
| 89 |
"train_batch_size": 2,
|
| 90 |
"trial_name": null,
|
| 91 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
"best_metric": null,
|
| 3 |
"best_model_checkpoint": null,
|
| 4 |
+
"epoch": 0.0018502265341461678,
|
| 5 |
"eval_steps": 10,
|
| 6 |
+
"global_step": 39,
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
|
|
| 66 |
"learning_rate": 6.91341716182545e-05,
|
| 67 |
"loss": 5.618,
|
| 68 |
"step": 25
|
| 69 |
+
},
|
| 70 |
+
{
|
| 71 |
+
"epoch": 0.0014232511801124368,
|
| 72 |
+
"grad_norm": 8.83657169342041,
|
| 73 |
+
"learning_rate": 5e-05,
|
| 74 |
+
"loss": 5.6481,
|
| 75 |
+
"step": 30
|
| 76 |
+
},
|
| 77 |
+
{
|
| 78 |
+
"epoch": 0.0014232511801124368,
|
| 79 |
+
"eval_loss": 1.3377556800842285,
|
| 80 |
+
"eval_runtime": 616.2304,
|
| 81 |
+
"eval_samples_per_second": 14.404,
|
| 82 |
+
"eval_steps_per_second": 7.202,
|
| 83 |
+
"step": 30
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.0016604597101311763,
|
| 87 |
+
"grad_norm": 9.329240798950195,
|
| 88 |
+
"learning_rate": 3.086582838174551e-05,
|
| 89 |
+
"loss": 5.3622,
|
| 90 |
+
"step": 35
|
| 91 |
}
|
| 92 |
],
|
| 93 |
"logging_steps": 5,
|
|
|
|
| 107 |
"attributes": {}
|
| 108 |
}
|
| 109 |
},
|
| 110 |
+
"total_flos": 7580436142227456.0,
|
| 111 |
"train_batch_size": 2,
|
| 112 |
"trial_name": null,
|
| 113 |
"trial_params": null
|