Instructions to use shibajustfor/b93c8795-5087-436c-95c0-419f21c38c96 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shibajustfor/b93c8795-5087-436c-95c0-419f21c38c96 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2") model = PeftModel.from_pretrained(base_model, "shibajustfor/b93c8795-5087-436c-95c0-419f21c38c96") - 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 108113968
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0741e4ee01070f98d6c2ee589dbcac7b76201b76bab653eb5cda49fce61c4b91
|
| 3 |
size 108113968
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 55549892
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ba4a9547c30761f6436e07261b4fc47ea8108ddf21ff7b0cbe23780509c62cb4
|
| 3 |
size 55549892
|
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:ca89fdf7eb52eabc419a7130285a92b126f2937b0b06ee55c501a2dc14427ea4
|
| 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": 20.649,
|
| 145 |
"eval_steps_per_second": 10.324,
|
| 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": 0.3508771929824561,
|
| 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": 20.649,
|
| 145 |
"eval_steps_per_second": 10.324,
|
| 146 |
"step": 150
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.2807017543859649,
|
| 150 |
+
"grad_norm": 0.3036251664161682,
|
| 151 |
+
"learning_rate": 2.0055723659649904e-05,
|
| 152 |
+
"loss": 0.0091,
|
| 153 |
+
"step": 160
|
| 154 |
+
},
|
| 155 |
+
{
|
| 156 |
+
"epoch": 0.2982456140350877,
|
| 157 |
+
"grad_norm": 0.2512568533420563,
|
| 158 |
+
"learning_rate": 1.1454397434679021e-05,
|
| 159 |
+
"loss": 0.0092,
|
| 160 |
+
"step": 170
|
| 161 |
+
},
|
| 162 |
+
{
|
| 163 |
+
"epoch": 0.3157894736842105,
|
| 164 |
+
"grad_norm": 0.2012607902288437,
|
| 165 |
+
"learning_rate": 5.146355805285452e-06,
|
| 166 |
+
"loss": 0.0058,
|
| 167 |
+
"step": 180
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.3333333333333333,
|
| 171 |
+
"grad_norm": 0.46869468688964844,
|
| 172 |
+
"learning_rate": 1.2949737362087156e-06,
|
| 173 |
+
"loss": 0.0063,
|
| 174 |
+
"step": 190
|
| 175 |
+
},
|
| 176 |
+
{
|
| 177 |
+
"epoch": 0.3508771929824561,
|
| 178 |
+
"grad_norm": 0.19013503193855286,
|
| 179 |
+
"learning_rate": 0.0,
|
| 180 |
+
"loss": 0.0031,
|
| 181 |
+
"step": 200
|
| 182 |
+
},
|
| 183 |
+
{
|
| 184 |
+
"epoch": 0.3508771929824561,
|
| 185 |
+
"eval_loss": 0.00592783885076642,
|
| 186 |
+
"eval_runtime": 11.6387,
|
| 187 |
+
"eval_samples_per_second": 20.621,
|
| 188 |
+
"eval_steps_per_second": 10.31,
|
| 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": 4.10478723465216e+16,
|
| 210 |
"train_batch_size": 2,
|
| 211 |
"trial_name": null,
|
| 212 |
"trial_params": null
|