Instructions to use Shaer-AI/ARBERT-base-submeter-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shaer-AI/ARBERT-base-submeter-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shaer-AI/ARBERT-base-submeter-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier") model = AutoModelForSequenceClassification.from_pretrained("Shaer-AI/ARBERT-base-submeter-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1500, 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 651465828
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:647fed4e04ad26ebb3c784d1a356a784a9637958334db3eb5d0316be84f6d5e8
|
| 3 |
size 651465828
|
last-checkpoint/optimizer.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1303053067
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:757e6258c732d8be296ea401a064e7d047e5fe243b906b0fe02527d2b65887e0
|
| 3 |
size 1303053067
|
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:dce76db4209fed0144afb633123692a9504a05f46b5db395d330022dd387107c
|
| 3 |
size 14645
|
last-checkpoint/scaler.pt
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1383
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ca372268f4fa9335030c0cb7aedb6cdba75f457da50e7a4034abb1a2d0843689
|
| 3 |
size 1383
|
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 sha256:1d83883040b01510c2a7a674131a901f107e1b441c0ea6574a16489cefbc3e2d
|
| 3 |
size 1465
|
last-checkpoint/trainer_state.json
CHANGED
|
@@ -1,10 +1,10 @@
|
|
| 1 |
{
|
| 2 |
-
"best_global_step":
|
| 3 |
-
"best_metric": 0.
|
| 4 |
-
"best_model_checkpoint": "/kaggle/working/arbert_submeter_training/checkpoints/checkpoint-
|
| 5 |
-
"epoch": 0.
|
| 6 |
"eval_steps": 500,
|
| 7 |
-
"global_step":
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
@@ -44,6 +44,24 @@
|
|
| 44 |
"eval_steps_per_second": 3.458,
|
| 45 |
"eval_weighted_f1": 0.8676584583901654,
|
| 46 |
"step": 1000
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 47 |
}
|
| 48 |
],
|
| 49 |
"logging_steps": 500,
|
|
@@ -63,7 +81,7 @@
|
|
| 63 |
"attributes": {}
|
| 64 |
}
|
| 65 |
},
|
| 66 |
-
"total_flos":
|
| 67 |
"train_batch_size": 128,
|
| 68 |
"trial_name": null,
|
| 69 |
"trial_params": null
|
|
|
|
| 1 |
{
|
| 2 |
+
"best_global_step": 1500,
|
| 3 |
+
"best_metric": 0.9137351351351352,
|
| 4 |
+
"best_model_checkpoint": "/kaggle/working/arbert_submeter_training/checkpoints/checkpoint-1500",
|
| 5 |
+
"epoch": 0.25944824007610484,
|
| 6 |
"eval_steps": 500,
|
| 7 |
+
"global_step": 1500,
|
| 8 |
"is_hyper_param_search": false,
|
| 9 |
"is_local_process_zero": true,
|
| 10 |
"is_world_process_zero": true,
|
|
|
|
| 44 |
"eval_steps_per_second": 3.458,
|
| 45 |
"eval_weighted_f1": 0.8676584583901654,
|
| 46 |
"step": 1000
|
| 47 |
+
},
|
| 48 |
+
{
|
| 49 |
+
"epoch": 0.25944824007610484,
|
| 50 |
+
"grad_norm": 6.3231658935546875,
|
| 51 |
+
"learning_rate": 4.567911910526923e-05,
|
| 52 |
+
"loss": 0.3789,
|
| 53 |
+
"step": 1500
|
| 54 |
+
},
|
| 55 |
+
{
|
| 56 |
+
"epoch": 0.25944824007610484,
|
| 57 |
+
"eval_accuracy": 0.9137351351351352,
|
| 58 |
+
"eval_loss": 0.2946445643901825,
|
| 59 |
+
"eval_macro_f1": 0.47816321808462303,
|
| 60 |
+
"eval_runtime": 418.8729,
|
| 61 |
+
"eval_samples_per_second": 883.323,
|
| 62 |
+
"eval_steps_per_second": 3.452,
|
| 63 |
+
"eval_weighted_f1": 0.9066607985127312,
|
| 64 |
+
"step": 1500
|
| 65 |
}
|
| 66 |
],
|
| 67 |
"logging_steps": 500,
|
|
|
|
| 81 |
"attributes": {}
|
| 82 |
}
|
| 83 |
},
|
| 84 |
+
"total_flos": 6315969355776000.0,
|
| 85 |
"train_batch_size": 128,
|
| 86 |
"trial_name": null,
|
| 87 |
"trial_params": null
|