Text Classification
Transformers
Safetensors
English
multilingual
xlm-roberta
multi-label-classification
multi-head-classification
disaster-response
humanitarian-aid
social-media
twitter
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use spencercdz/xlm-roberta-sentiment-requests with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use spencercdz/xlm-roberta-sentiment-requests with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="spencercdz/xlm-roberta-sentiment-requests")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("spencercdz/xlm-roberta-sentiment-requests") model = AutoModel.from_pretrained("spencercdz/xlm-roberta-sentiment-requests", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 582
Browse files- model.safetensors +1 -1
- training_log.csv +1 -0
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1109972056
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d5d45feaead297432d801b5b423200cafdc1287169777e9ec12e01ddaf93aae8
|
| 3 |
size 1109972056
|
training_log.csv
CHANGED
|
@@ -580,3 +580,4 @@ epoch,eval_f1_macro,eval_f1_micro,eval_loss,eval_runtime,eval_samples_per_second
|
|
| 580 |
579.0,0.3497931758468584,0.7237755304382312,0.14662408828735352,14.5149,177.266,5.58,0.26039642440730665,380982
|
| 581 |
580.0,0.3498016783996152,0.7237188073622067,0.14655892550945282,14.4433,178.145,5.608,0.26000777302759426,381640
|
| 582 |
581.0,0.35003747958417086,0.7238180284764598,0.1465616524219513,14.5994,176.241,5.548,0.26000777302759426,382298
|
|
|
|
|
|
| 580 |
579.0,0.3497931758468584,0.7237755304382312,0.14662408828735352,14.5149,177.266,5.58,0.26039642440730665,380982
|
| 581 |
580.0,0.3498016783996152,0.7237188073622067,0.14655892550945282,14.4433,178.145,5.608,0.26000777302759426,381640
|
| 582 |
581.0,0.35003747958417086,0.7238180284764598,0.1465616524219513,14.5994,176.241,5.548,0.26000777302759426,382298
|
| 583 |
+
582.0,0.35031943220443923,0.7238095238095238,0.1465374082326889,14.3623,179.15,5.64,0.26039642440730665,382956
|