Instructions to use CodeIsAbstract/HybridModelScratch_ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeIsAbstract/HybridModelScratch_ with Transformers:
# Load model directly from transformers import HybridFourierLM model = HybridFourierLM.from_pretrained("CodeIsAbstract/HybridModelScratch_", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 600, checkpoint
Browse files
last-checkpoint/model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 579824888
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:28169bb183740976fb1e1012281faf4daaa901f0809070b5431b167a9aed9330
|
| 3 |
size 579824888
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1159794763
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5bcc09d2987fc871b0f3d765698df5a7ddb67b242d4bf83d5e4d4194e97c62f1
|
| 3 |
size 1159794763
|
last-checkpoint/rng_state.pth
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 14645
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ecde0592a54835c0791d413df0b84cfe61c8375c6c53371a3a262f4a720ce7ee
|
| 3 |
size 14645
|
last-checkpoint/scheduler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1465
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bff1f3af0c59bc6ebaa29224579d5dfcd2f5ed0cc9dfc92a0a059a14be64f7bc
|
| 3 |
size 1465
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -2,9 +2,9 @@
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
-
"epoch": 0.
|
| 6 |
"eval_steps": 100,
|
| 7 |
-
"global_step":
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
@@ -100,6 +100,52 @@
|
|
| 100 |
"eval_samples_per_second": 73.776,
|
| 101 |
"eval_steps_per_second": 4.64,
|
| 102 |
"step": 400
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 103 |
}
|
| 104 |
],
|
| 105 |
"logging_steps": 50,
|
|
@@ -119,7 +165,7 @@
|
|
| 119 |
"attributes": {}
|
| 120 |
}
|
| 121 |
},
|
| 122 |
-
"total_flos":
|
| 123 |
"train_batch_size": 64,
|
| 124 |
"trial_name": null,
|
| 125 |
"trial_params": null
|
|
|
|
| 2 |
"best_global_step": null,
|
| 3 |
"best_metric": null,
|
| 4 |
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 0.6,
|
| 6 |
"eval_steps": 100,
|
| 7 |
+
"global_step": 600,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 100 |
"eval_samples_per_second": 73.776,
|
| 101 |
"eval_steps_per_second": 4.64,
|
| 102 |
"step": 400
|
| 103 |
+
},
|
| 104 |
+
{
|
| 105 |
+
"epoch": 0.45,
|
| 106 |
+
"grad_norm": 2.3908166885375977,
|
| 107 |
+
"learning_rate": 7.24521909782041e-05,
|
| 108 |
+
"loss": 22.8638,
|
| 109 |
+
"step": 450
|
| 110 |
+
},
|
| 111 |
+
{
|
| 112 |
+
"epoch": 0.5,
|
| 113 |
+
"grad_norm": 2.105929136276245,
|
| 114 |
+
"learning_rate": 6.386080060392754e-05,
|
| 115 |
+
"loss": 22.5651,
|
| 116 |
+
"step": 500
|
| 117 |
+
},
|
| 118 |
+
{
|
| 119 |
+
"epoch": 0.5,
|
| 120 |
+
"eval_accuracy": 0.20586229645784704,
|
| 121 |
+
"eval_loss": 5.55440616607666,
|
| 122 |
+
"eval_runtime": 13.4924,
|
| 123 |
+
"eval_samples_per_second": 71.892,
|
| 124 |
+
"eval_steps_per_second": 4.521,
|
| 125 |
+
"step": 500
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.55,
|
| 129 |
+
"grad_norm": 2.184967041015625,
|
| 130 |
+
"learning_rate": 5.479739728928219e-05,
|
| 131 |
+
"loss": 22.2741,
|
| 132 |
+
"step": 550
|
| 133 |
+
},
|
| 134 |
+
{
|
| 135 |
+
"epoch": 0.6,
|
| 136 |
+
"grad_norm": 2.2348268032073975,
|
| 137 |
+
"learning_rate": 4.5570624363794226e-05,
|
| 138 |
+
"loss": 22.0473,
|
| 139 |
+
"step": 600
|
| 140 |
+
},
|
| 141 |
+
{
|
| 142 |
+
"epoch": 0.6,
|
| 143 |
+
"eval_accuracy": 0.21187852939218293,
|
| 144 |
+
"eval_loss": 5.435864448547363,
|
| 145 |
+
"eval_runtime": 12.3748,
|
| 146 |
+
"eval_samples_per_second": 78.385,
|
| 147 |
+
"eval_steps_per_second": 4.929,
|
| 148 |
+
"step": 600
|
| 149 |
}
|
| 150 |
],
|
| 151 |
"logging_steps": 50,
|
|
|
|
| 165 |
"attributes": {}
|
| 166 |
}
|
| 167 |
},
|
| 168 |
+
"total_flos": 1.003509981904896e+17,
|
| 169 |
"train_batch_size": 64,
|
| 170 |
"trial_name": null,
|
| 171 |
"trial_params": null
|