Instructions to use LexFerrinson/FirulaiModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LexFerrinson/FirulaiModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LexFerrinson/FirulaiModel")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LexFerrinson/FirulaiModel") model = AutoModelForTokenClassification.from_pretrained("LexFerrinson/FirulaiModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
b12675b
1
Parent(s): 81f4025
Training in progress epoch 0
Browse files- README.md +5 -7
- config.json +1 -1
- tf_model.h5 +1 -1
README.md
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
-
base_model:
|
| 4 |
tags:
|
| 5 |
- generated_from_keras_callback
|
| 6 |
model-index:
|
|
@@ -13,15 +13,15 @@ probably proofread and complete it, then remove this comment. -->
|
|
| 13 |
|
| 14 |
# LexFerrinson/FirulaiModel
|
| 15 |
|
| 16 |
-
This model is a fine-tuned version of [
|
| 17 |
It achieves the following results on the evaluation set:
|
| 18 |
-
- Train Loss: 0.
|
| 19 |
- Validation Loss: 0.7565
|
| 20 |
- Train Precision: 0.0
|
| 21 |
- Train Recall: 0.0
|
| 22 |
- Train F1: 0.0
|
| 23 |
- Train Accuracy: 0.9082
|
| 24 |
-
- Epoch:
|
| 25 |
|
| 26 |
## Model description
|
| 27 |
|
|
@@ -47,9 +47,7 @@ The following hyperparameters were used during training:
|
|
| 47 |
|
| 48 |
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|
| 49 |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
|
| 50 |
-
|
|
| 51 |
-
| 0.9005 | 0.8023 | 0.0 | 0.0 | 0.0 | 0.9019 | 1 |
|
| 52 |
-
| 0.8084 | 0.7565 | 0.0 | 0.0 | 0.0 | 0.9082 | 2 |
|
| 53 |
|
| 54 |
|
| 55 |
### Framework versions
|
|
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
+
base_model: FirulAI/FirstModel
|
| 4 |
tags:
|
| 5 |
- generated_from_keras_callback
|
| 6 |
model-index:
|
|
|
|
| 13 |
|
| 14 |
# LexFerrinson/FirulaiModel
|
| 15 |
|
| 16 |
+
This model is a fine-tuned version of [FirulAI/FirstModel](https://huggingface.co/FirulAI/FirstModel) on an unknown dataset.
|
| 17 |
It achieves the following results on the evaluation set:
|
| 18 |
+
- Train Loss: 0.7652
|
| 19 |
- Validation Loss: 0.7565
|
| 20 |
- Train Precision: 0.0
|
| 21 |
- Train Recall: 0.0
|
| 22 |
- Train F1: 0.0
|
| 23 |
- Train Accuracy: 0.9082
|
| 24 |
+
- Epoch: 0
|
| 25 |
|
| 26 |
## Model description
|
| 27 |
|
|
|
|
| 47 |
|
| 48 |
| Train Loss | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
|
| 49 |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
|
| 50 |
+
| 0.7652 | 0.7565 | 0.0 | 0.0 | 0.0 | 0.9082 | 0 |
|
|
|
|
|
|
|
| 51 |
|
| 52 |
|
| 53 |
### Framework versions
|
config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
"activation": "gelu",
|
| 4 |
"architectures": [
|
| 5 |
"DistilBertForTokenClassification"
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "FirulAI/FirstModel",
|
| 3 |
"activation": "gelu",
|
| 4 |
"architectures": [
|
| 5 |
"DistilBertForTokenClassification"
|
tf_model.h5
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 265587984
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c5151199966e83f1458779685692032be6228f2705956afefbedc294b2971f4c
|
| 3 |
size 265587984
|