Instructions to use fmnxl/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fmnxl/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fmnxl/output")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fmnxl/output") model = AutoModelForTokenClassification.from_pretrained("fmnxl/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +10 -10
- model.safetensors +1 -1
- training_args.bin +1 -1
README.md
CHANGED
|
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 21 |
|
| 22 |
This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on the None dataset.
|
| 23 |
It achieves the following results on the evaluation set:
|
| 24 |
-
- Loss: 0.
|
| 25 |
-
- Precision: 0.
|
| 26 |
-
- Recall: 0.
|
| 27 |
-
- F1: 0.
|
| 28 |
-
- Accuracy: 0.
|
| 29 |
|
| 30 |
## Model description
|
| 31 |
|
|
@@ -58,11 +58,11 @@ The following hyperparameters were used during training:
|
|
| 58 |
|
| 59 |
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 60 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 61 |
-
| 0.
|
| 62 |
-
| 0.
|
| 63 |
-
| 0.
|
| 64 |
-
| 0.
|
| 65 |
-
| 0.
|
| 66 |
|
| 67 |
|
| 68 |
### Framework versions
|
|
|
|
| 21 |
|
| 22 |
This model is a fine-tuned version of [jhu-clsp/mmBERT-base](https://huggingface.co/jhu-clsp/mmBERT-base) on the None dataset.
|
| 23 |
It achieves the following results on the evaluation set:
|
| 24 |
+
- Loss: 0.5401
|
| 25 |
+
- Precision: 0.6247
|
| 26 |
+
- Recall: 0.7248
|
| 27 |
+
- F1: 0.6710
|
| 28 |
+
- Accuracy: 0.7611
|
| 29 |
|
| 30 |
## Model description
|
| 31 |
|
|
|
|
| 58 |
|
| 59 |
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 60 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 61 |
+
| 0.6289 | 1.0 | 438 | 0.5958 | 0.5893 | 0.7268 | 0.6509 | 0.7581 |
|
| 62 |
+
| 0.5744 | 2.0 | 876 | 0.5607 | 0.6160 | 0.6992 | 0.6549 | 0.7537 |
|
| 63 |
+
| 0.5158 | 3.0 | 1314 | 0.5401 | 0.6247 | 0.7248 | 0.6710 | 0.7611 |
|
| 64 |
+
| 0.4314 | 4.0 | 1752 | 0.5914 | 0.6224 | 0.7129 | 0.6646 | 0.7320 |
|
| 65 |
+
| 0.382 | 5.0 | 2190 | 0.6142 | 0.6039 | 0.7154 | 0.6549 | 0.7675 |
|
| 66 |
|
| 67 |
|
| 68 |
### Framework versions
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1230156812
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:592ee503bdbc3b982a97a2660354deff9a974d2c4e3487d69251f6d999513956
|
| 3 |
size 1230156812
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 5841
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9486648c8742168f5533e637d48fe7ceb7099281f105bc1e16cddd2f3a39ded0
|
| 3 |
size 5841
|