Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use V12X-ksr/FOCALtrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use V12X-ksr/FOCALtrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="V12X-ksr/FOCALtrain")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("V12X-ksr/FOCALtrain") model = AutoModelForSequenceClassification.from_pretrained("V12X-ksr/FOCALtrain") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
CHANGED
|
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 15 |
|
| 16 |
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
|
| 17 |
It achieves the following results on the evaluation set:
|
| 18 |
-
- Loss:
|
| 19 |
|
| 20 |
## Model description
|
| 21 |
|
|
@@ -41,22 +41,25 @@ The following hyperparameters were used during training:
|
|
| 41 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 42 |
- lr_scheduler_type: linear
|
| 43 |
- lr_scheduler_warmup_steps: 500
|
| 44 |
-
- num_epochs:
|
| 45 |
|
| 46 |
### Training results
|
| 47 |
|
| 48 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 49 |
|:-------------:|:-----:|:----:|:---------------:|
|
| 50 |
-
|
|
| 51 |
-
| 0.
|
| 52 |
-
|
|
| 53 |
-
| 0.
|
| 54 |
-
| 0.
|
|
|
|
|
|
|
|
|
|
| 55 |
|
| 56 |
|
| 57 |
### Framework versions
|
| 58 |
|
| 59 |
- Transformers 4.35.2
|
| 60 |
- Pytorch 2.1.0+cu121
|
| 61 |
-
- Datasets 2.
|
| 62 |
- Tokenizers 0.15.1
|
|
|
|
| 15 |
|
| 16 |
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
|
| 17 |
It achieves the following results on the evaluation set:
|
| 18 |
+
- Loss: 1.2758
|
| 19 |
|
| 20 |
## Model description
|
| 21 |
|
|
|
|
| 41 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 42 |
- lr_scheduler_type: linear
|
| 43 |
- lr_scheduler_warmup_steps: 500
|
| 44 |
+
- num_epochs: 8
|
| 45 |
|
| 46 |
### Training results
|
| 47 |
|
| 48 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 49 |
|:-------------:|:-----:|:----:|:---------------:|
|
| 50 |
+
| 1.3121 | 1.0 | 474 | 1.3494 |
|
| 51 |
+
| 0.9964 | 2.0 | 948 | 1.3077 |
|
| 52 |
+
| 1.0453 | 3.0 | 1422 | 1.2758 |
|
| 53 |
+
| 0.6379 | 4.0 | 1896 | 1.5232 |
|
| 54 |
+
| 0.765 | 5.0 | 2370 | 1.5891 |
|
| 55 |
+
| 0.2287 | 6.0 | 2844 | 2.2163 |
|
| 56 |
+
| 0.1243 | 7.0 | 3318 | 2.5331 |
|
| 57 |
+
| 0.1699 | 8.0 | 3792 | 2.7521 |
|
| 58 |
|
| 59 |
|
| 60 |
### Framework versions
|
| 61 |
|
| 62 |
- Transformers 4.35.2
|
| 63 |
- Pytorch 2.1.0+cu121
|
| 64 |
+
- Datasets 2.17.0
|
| 65 |
- Tokenizers 0.15.1
|
logs/events.out.tfevents.1707940688.6c734d94b679.464.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:28a54ffad40f7c39668d4ec17038d12308094f207f0d0ad5a5fbf89e05fa4874
|
| 3 |
+
size 66401
|
logs/events.out.tfevents.1707942155.6c734d94b679.464.1
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a4d913d02f9bd98b517945d28ae1f5d4777ba795a20498d5515ec324735c4879
|
| 3 |
+
size 359
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498631280
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:de5b46052d724f81f883263b9004f5d230699d3eb75e7cdda0cdbc6dfe865db7
|
| 3 |
size 498631280
|