update model card README.md

README.md

@@ -0,0 +1,108 @@
+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- favsbot
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: camembert-base-NER-favsbot
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: favsbot
+      type: favsbot
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.6
+    - name: Recall
+      type: recall
+      value: 0.012145748987854251
+    - name: F1
+      type: f1
+      value: 0.023809523809523808
+    - name: Accuracy
+      type: accuracy
+      value: 0.42078364565587734
+---
+
+<!-- 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. -->
+
+# camembert-base-NER-favsbot
+
+This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the favsbot dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7433
+- Precision: 0.6
+- Recall: 0.0121
+- F1: 0.0238
+- Accuracy: 0.4208
+
+## 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: 1.5e-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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 4    | 2.2915          | 0.1364    | 0.1215 | 0.1285 | 0.3475   |
+| No log        | 2.0   | 8    | 2.2230          | 0.2909    | 0.0648 | 0.1060 | 0.4395   |
+| No log        | 3.0   | 12   | 2.1573          | 0.4545    | 0.0202 | 0.0388 | 0.4225   |
+| No log        | 4.0   | 16   | 2.0961          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 5.0   | 20   | 2.0426          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 6.0   | 24   | 1.9965          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 7.0   | 28   | 1.9575          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 8.0   | 32   | 1.9233          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 9.0   | 36   | 1.8933          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 10.0  | 40   | 1.8674          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 11.0  | 44   | 1.8441          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 12.0  | 48   | 1.8240          | 0.0       | 0.0    | 0.0    | 0.4123   |
+| No log        | 13.0  | 52   | 1.8060          | 1.0       | 0.0040 | 0.0081 | 0.4140   |
+| No log        | 14.0  | 56   | 1.7899          | 1.0       | 0.0040 | 0.0081 | 0.4140   |
+| No log        | 15.0  | 60   | 1.7762          | 1.0       | 0.0040 | 0.0081 | 0.4140   |
+| No log        | 16.0  | 64   | 1.7647          | 0.5       | 0.0040 | 0.0080 | 0.4157   |
+| No log        | 17.0  | 68   | 1.7556          | 0.5       | 0.0040 | 0.0080 | 0.4157   |
+| No log        | 18.0  | 72   | 1.7490          | 0.6667    | 0.0081 | 0.016  | 0.4174   |
+| No log        | 19.0  | 76   | 1.7449          | 0.75      | 0.0121 | 0.0239 | 0.4191   |
+| No log        | 20.0  | 80   | 1.7433          | 0.6       | 0.0121 | 0.0238 | 0.4208   |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.1
+- Datasets 2.4.0
+- Tokenizers 0.12.1