Instructions to use kk-aivio/cd52ae9a-9eb7-4cfe-bdad-e281fa438605 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kk-aivio/cd52ae9a-9eb7-4cfe-bdad-e281fa438605 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Orenguteng/Llama-3-8B-Lexi-Uncensored") model = PeftModel.from_pretrained(base_model, "kk-aivio/cd52ae9a-9eb7-4cfe-bdad-e281fa438605") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 200, 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 sha256:9f8232d71b04ea9fb82001782fda2a6809f9aa0e6de1d05283df2767a17579a6
|
| 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 sha256:0a125e64d7028e2fc972a34eb3bcb0a22c54863264cdaa04ccd3eccb551ac232
|
| 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 sha256:6e39d3bd6aca35d9c2c4af115bc55fc6bc26ea5767dd3a367c3979f22ceabe3d
|
| 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:ca9a25c72339c898b564e0c464a3f6fc75bbeec408008928b7ed05533156b98c
|
| 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": 50,
|
| 6 |
-
"global_step":
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
@@ -144,6 +144,49 @@
|
|
| 144 |
"eval_samples_per_second": 30.582,
|
| 145 |
"eval_steps_per_second": 15.291,
|
| 146 |
"step": 150
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 147 |
}
|
| 148 |
],
|
| 149 |
"logging_steps": 10,
|
|
@@ -158,12 +201,12 @@
|
|
| 158 |
"should_evaluate": false,
|
| 159 |
"should_log": false,
|
| 160 |
"should_save": true,
|
| 161 |
-
"should_training_stop":
|
| 162 |
},
|
| 163 |
"attributes": {}
|
| 164 |
}
|
| 165 |
},
|
| 166 |
-
"total_flos":
|
| 167 |
"train_batch_size": 2,
|
| 168 |
"trial_name": null,
|
| 169 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
"best_metric": null,
|
| 3 |
"best_model_checkpoint": null,
|
| 4 |
+
"epoch": 0.29038112522686027,
|
| 5 |
"eval_steps": 50,
|
| 6 |
+
"global_step": 200,
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
|
|
| 144 |
"eval_samples_per_second": 30.582,
|
| 145 |
"eval_steps_per_second": 15.291,
|
| 146 |
"step": 150
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.2323049001814882,
|
| 150 |
+
"grad_norm": 9.756109237670898,
|
| 151 |
+
"learning_rate": 2.0055723659649904e-05,
|
| 152 |
+
"loss": 3.0355,
|
| 153 |
+
"step": 160
|
| 154 |
+
},
|
| 155 |
+
{
|
| 156 |
+
"epoch": 0.24682395644283123,
|
| 157 |
+
"grad_norm": 6.9620466232299805,
|
| 158 |
+
"learning_rate": 1.1454397434679021e-05,
|
| 159 |
+
"loss": 1.9431,
|
| 160 |
+
"step": 170
|
| 161 |
+
},
|
| 162 |
+
{
|
| 163 |
+
"epoch": 0.2613430127041742,
|
| 164 |
+
"grad_norm": 7.356261730194092,
|
| 165 |
+
"learning_rate": 5.146355805285452e-06,
|
| 166 |
+
"loss": 1.8571,
|
| 167 |
+
"step": 180
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.27586206896551724,
|
| 171 |
+
"grad_norm": 6.641462326049805,
|
| 172 |
+
"learning_rate": 1.2949737362087156e-06,
|
| 173 |
+
"loss": 2.0129,
|
| 174 |
+
"step": 190
|
| 175 |
+
},
|
| 176 |
+
{
|
| 177 |
+
"epoch": 0.29038112522686027,
|
| 178 |
+
"grad_norm": 7.481417655944824,
|
| 179 |
+
"learning_rate": 0.0,
|
| 180 |
+
"loss": 2.2513,
|
| 181 |
+
"step": 200
|
| 182 |
+
},
|
| 183 |
+
{
|
| 184 |
+
"epoch": 0.29038112522686027,
|
| 185 |
+
"eval_loss": 1.837255835533142,
|
| 186 |
+
"eval_runtime": 9.5016,
|
| 187 |
+
"eval_samples_per_second": 30.521,
|
| 188 |
+
"eval_steps_per_second": 15.261,
|
| 189 |
+
"step": 200
|
| 190 |
}
|
| 191 |
],
|
| 192 |
"logging_steps": 10,
|
|
|
|
| 201 |
"should_evaluate": false,
|
| 202 |
"should_log": false,
|
| 203 |
"should_save": true,
|
| 204 |
+
"should_training_stop": true
|
| 205 |
},
|
| 206 |
"attributes": {}
|
| 207 |
}
|
| 208 |
},
|
| 209 |
+
"total_flos": 3.69912849629184e+16,
|
| 210 |
"train_batch_size": 2,
|
| 211 |
"trial_name": null,
|
| 212 |
"trial_params": null
|