Instructions to use havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("fxmarty/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "havinash-ai/d72a532e-30dd-4e65-afb4-480183732f0a") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 250, 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 26008
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9884b9c786aae4699e10cf282d40cb5f1c50e6f1cb2e8bd354d1213c172521ee
|
| 3 |
size 26008
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 61926
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:370d2de3f96e560118243db6b309a03a3381afb0af56c61acf47ca87aef9121a
|
| 3 |
size 61926
|
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:e2edc0261f7034ce0d71cea4f289a97e7923584b1d4870351bbf4900337528d8
|
| 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 sha256:6088f970b1f0429ad85e576795204ef9269ce142d6ce9c2595b5649efde833b6
|
| 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": 63,
|
| 6 |
-
"global_step":
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
@@ -165,6 +165,55 @@
|
|
| 165 |
"eval_samples_per_second": 222.85,
|
| 166 |
"eval_steps_per_second": 111.425,
|
| 167 |
"step": 189
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 168 |
}
|
| 169 |
],
|
| 170 |
"logging_steps": 10,
|
|
@@ -179,12 +228,12 @@
|
|
| 179 |
"should_evaluate": false,
|
| 180 |
"should_log": false,
|
| 181 |
"should_save": true,
|
| 182 |
-
"should_training_stop":
|
| 183 |
},
|
| 184 |
"attributes": {}
|
| 185 |
}
|
| 186 |
},
|
| 187 |
-
"total_flos":
|
| 188 |
"train_batch_size": 2,
|
| 189 |
"trial_name": null,
|
| 190 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
"best_metric": null,
|
| 3 |
"best_model_checkpoint": null,
|
| 4 |
+
"epoch": 0.0576036866359447,
|
| 5 |
"eval_steps": 63,
|
| 6 |
+
"global_step": 250,
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
|
|
| 165 |
"eval_samples_per_second": 222.85,
|
| 166 |
"eval_steps_per_second": 111.425,
|
| 167 |
"step": 189
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.04377880184331797,
|
| 171 |
+
"grad_norm": 0.07347025722265244,
|
| 172 |
+
"learning_rate": 2.8165064990227252e-05,
|
| 173 |
+
"loss": 11.9135,
|
| 174 |
+
"step": 190
|
| 175 |
+
},
|
| 176 |
+
{
|
| 177 |
+
"epoch": 0.04608294930875576,
|
| 178 |
+
"grad_norm": 0.059106022119522095,
|
| 179 |
+
"learning_rate": 1.985863781320435e-05,
|
| 180 |
+
"loss": 11.9135,
|
| 181 |
+
"step": 200
|
| 182 |
+
},
|
| 183 |
+
{
|
| 184 |
+
"epoch": 0.04838709677419355,
|
| 185 |
+
"grad_norm": 0.09761878848075867,
|
| 186 |
+
"learning_rate": 1.286812958766106e-05,
|
| 187 |
+
"loss": 11.9121,
|
| 188 |
+
"step": 210
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.05069124423963134,
|
| 192 |
+
"grad_norm": 0.0723123848438263,
|
| 193 |
+
"learning_rate": 7.308324265397836e-06,
|
| 194 |
+
"loss": 11.9143,
|
| 195 |
+
"step": 220
|
| 196 |
+
},
|
| 197 |
+
{
|
| 198 |
+
"epoch": 0.052995391705069124,
|
| 199 |
+
"grad_norm": 0.05200246348977089,
|
| 200 |
+
"learning_rate": 3.270513696097055e-06,
|
| 201 |
+
"loss": 11.9119,
|
| 202 |
+
"step": 230
|
| 203 |
+
},
|
| 204 |
+
{
|
| 205 |
+
"epoch": 0.055299539170506916,
|
| 206 |
+
"grad_norm": 0.06363704055547714,
|
| 207 |
+
"learning_rate": 8.209986176753948e-07,
|
| 208 |
+
"loss": 11.9129,
|
| 209 |
+
"step": 240
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.0576036866359447,
|
| 213 |
+
"grad_norm": 0.07390929013490677,
|
| 214 |
+
"learning_rate": 0.0,
|
| 215 |
+
"loss": 11.9155,
|
| 216 |
+
"step": 250
|
| 217 |
}
|
| 218 |
],
|
| 219 |
"logging_steps": 10,
|
|
|
|
| 228 |
"should_evaluate": false,
|
| 229 |
"should_log": false,
|
| 230 |
"should_save": true,
|
| 231 |
+
"should_training_stop": true
|
| 232 |
},
|
| 233 |
"attributes": {}
|
| 234 |
}
|
| 235 |
},
|
| 236 |
+
"total_flos": 30681415680.0,
|
| 237 |
"train_batch_size": 2,
|
| 238 |
"trial_name": null,
|
| 239 |
"trial_params": null
|