update model card README.md

README.md

@@ -0,0 +1,86 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- financial_phrasebank
+metrics:
+- recall
+- accuracy
+- precision
+model-index:
+- name: financial_sentiment_model
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: financial_phrasebank
+      type: financial_phrasebank
+      args: sentences_50agree
+    metrics:
+    - name: Recall
+      type: recall
+      value: 0.8839956357328868
+    - name: Accuracy
+      type: accuracy
+      value: 0.8804123711340206
+    - name: Precision
+      type: precision
+      value: 0.8604175202419276
+---
+
+<!-- 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. -->
+
+# financial_sentiment_model
+
+This model is a fine-tuned version of [deepmind/language-perceiver](https://huggingface.co/deepmind/language-perceiver) on the financial_phrasebank dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3467
+- Recall: 0.8840
+- Accuracy: 0.8804
+- Precision: 0.8604
+
+## 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
+- distributed_type: tpu
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Recall | Accuracy | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:---------:|
+| 0.4481        | 1.0   | 273  | 0.4035          | 0.8526 | 0.8433   | 0.7955    |
+| 0.4069        | 2.0   | 546  | 0.4478          | 0.8683 | 0.8289   | 0.8123    |
+| 0.2225        | 3.0   | 819  | 0.3167          | 0.8747 | 0.8680   | 0.8387    |
+| 0.1245        | 4.0   | 1092 | 0.3467          | 0.8840 | 0.8804   | 0.8604    |
+
+
+### Framework versions
+
+- Transformers 4.15.0
+- Pytorch 1.9.0+cu102
+- Datasets 1.17.0
+- Tokenizers 0.10.3