Model save

README.md

@@ -0,0 +1,91 @@
+---
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- cnec
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: CNEC_xlm-roberta-large
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: cnec
+      type: cnec
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8133086876155268
+    - name: Recall
+      type: recall
+      value: 0.8734491315136477
+    - name: F1
+      type: f1
+      value: 0.8423067719550132
+    - name: Accuracy
+      type: accuracy
+      value: 0.9756733021077283
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# CNEC_xlm-roberta-large
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1032
+- Precision: 0.8133
+- Recall: 0.8734
+- F1: 0.8423
+- Accuracy: 0.9757
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2857        | 1.12  | 500  | 0.1271          | 0.7641    | 0.8630 | 0.8105 | 0.9685   |
+| 0.0864        | 2.24  | 1000 | 0.1032          | 0.8133    | 0.8734 | 0.8423 | 0.9757   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

runs/Feb22_14-11-02_n32/events.out.tfevents.1708607479.n32.1102908.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5acd546cf4e2d174b062f77ce4b347c1b2c0fd3eaa0de53dbb0a0f79bcd86237
-size 6135
+oid sha256:06cfe91c8e969e7b6cbb883af749e3c0e9e5bfb6b7ddfb2661b5ac87ee897832
+size 6489