Instructions to use Paladiso/bb73a8ba-f2ad-4dad-a9e7-46da888461bc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Paladiso/bb73a8ba-f2ad-4dad-a9e7-46da888461bc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("samoline/d06bfecd-ea82-4f80-8b9f-98631e6886ba") model = PeftModel.from_pretrained(base_model, "Paladiso/bb73a8ba-f2ad-4dad-a9e7-46da888461bc") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 10, 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 51431872
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c657e577692dcda6b27be19689872dd8670ff2a85454f27c67a525f8db160077
|
| 3 |
size 51431872
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 26550260
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a9a771e22dab2c6781a5f0c7fa561fead45cecfcdd280ad150ef0f32d62bc83b
|
| 3 |
size 26550260
|
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 sha256:16f8dce4ea8db55fab98810852c3b7d6da325bbb69e21644a5658ad81a5d8213
|
| 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:bb578e75c11a81e85dda67a691f96ba4793a02960f1409fd3e1511aac873491a
|
| 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": 3,
|
| 6 |
-
"global_step":
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
@@ -94,6 +94,13 @@
|
|
| 94 |
"eval_samples_per_second": 17.565,
|
| 95 |
"eval_steps_per_second": 8.787,
|
| 96 |
"step": 9
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 97 |
}
|
| 98 |
],
|
| 99 |
"logging_steps": 1,
|
|
@@ -108,12 +115,12 @@
|
|
| 108 |
"should_evaluate": false,
|
| 109 |
"should_log": false,
|
| 110 |
"should_save": true,
|
| 111 |
-
"should_training_stop":
|
| 112 |
},
|
| 113 |
"attributes": {}
|
| 114 |
}
|
| 115 |
},
|
| 116 |
-
"total_flos":
|
| 117 |
"train_batch_size": 2,
|
| 118 |
"trial_name": null,
|
| 119 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
"best_metric": null,
|
| 3 |
"best_model_checkpoint": null,
|
| 4 |
+
"epoch": 0.002033657023742946,
|
| 5 |
"eval_steps": 3,
|
| 6 |
+
"global_step": 10,
|
| 7 |
"is_hyper_param_search": false,
|
| 8 |
"is_local_process_zero": true,
|
| 9 |
"is_world_process_zero": true,
|
|
|
|
| 94 |
"eval_samples_per_second": 17.565,
|
| 95 |
"eval_steps_per_second": 8.787,
|
| 96 |
"step": 9
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"epoch": 0.002033657023742946,
|
| 100 |
+
"grad_norm": 1.2431139945983887,
|
| 101 |
+
"learning_rate": 0.0002,
|
| 102 |
+
"loss": 1.2176,
|
| 103 |
+
"step": 10
|
| 104 |
}
|
| 105 |
],
|
| 106 |
"logging_steps": 1,
|
|
|
|
| 115 |
"should_evaluate": false,
|
| 116 |
"should_log": false,
|
| 117 |
"should_save": true,
|
| 118 |
+
"should_training_stop": true
|
| 119 |
},
|
| 120 |
"attributes": {}
|
| 121 |
}
|
| 122 |
},
|
| 123 |
+
"total_flos": 760832065536000.0,
|
| 124 |
"train_batch_size": 2,
|
| 125 |
"trial_name": null,
|
| 126 |
"trial_params": null
|