ShieldX
/

manovyadh-1.1B-v1-chat

@@ -12,199 +12,224 @@ language:
 metrics:
 - accuracy
 pipeline_tag: text-generation
 ---
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 metrics:
 - accuracy
 pipeline_tag: text-generation
+base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
 ---
+# Uploaded  model
+- **Developed by:** ShieldX
+- **License:** apache-2.0
+- **Finetuned from model :** TinyLlama/TinyLlama-1.1B-Chat-v1.0
+<style>
+  img{
+    width: 40vw;
+    height: auto;
+    margin: 0 auto;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+  }
+</style>
+# ShieldX/manovyadh-1.1B-v1
+Introducing ManoVyadh, A finetuned version of TinyLlama 1.1B Chat on Mental Health Counselling Dataset.
+<img class="custom-image" src="manovyadh.png" alt="BongLlama">
+# Model Details
+## Model Description
+ManoVyadh is a LLM for mental health counselling.
+# Uses
+## Direct Use
+- base model for further finetuning
+- for fun
+## Downstream Use
+- can be deployed with api
+- used to create webapp or app to show demo
+## Out-of-Scope Use
+- cannot be used for production purpose
+- not to be applied in real life health purpose
+- cannot be used to generate text for research or academic purposes
+# Bias, Risks, and Limitations
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
+# Training Details
+# Model Examination
+We will be further finetuning this model on large dataset to see how it performs
+# Environmental Impact
 Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+- **Hardware Type:** 1 X Tesla T4
+- **Hours used:** 0.48
+- **Cloud Provider:** Google Colab
+- **Compute Region:** India
+# Technical Specifications
+## Model Architecture and Objective
+Finetuned on Tiny-Llama 1.1B Chat model
+### Hardware
+1 X Tesla T4
+# training
+This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on [ShieldX/manovyadh-3.5k](https://huggingface.co/datasets/ShieldX/manovyadh-3.5k) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8587
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- learning_rate: 2.5e-05
+- train_batch_size: 2
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 400
+- mixed_precision_training: Native AMP
+-
+### Training results
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.5894        | 0.01  | 5    | 2.5428          |
+| 2.5283        | 0.02  | 10   | 2.5240          |
+| 2.5013        | 0.03  | 15   | 2.5033          |
+| 2.378         | 0.05  | 20   | 2.4770          |
+| 2.3735        | 0.06  | 25   | 2.4544          |
+| 2.3894        | 0.07  | 30   | 2.4335          |
+| 2.403         | 0.08  | 35   | 2.4098          |
+| 2.3719        | 0.09  | 40   | 2.3846          |
+| 2.3691        | 0.1   | 45   | 2.3649          |
+| 2.3088        | 0.12  | 50   | 2.3405          |
+| 2.3384        | 0.13  | 55   | 2.3182          |
+| 2.2577        | 0.14  | 60   | 2.2926          |
+| 2.245         | 0.15  | 65   | 2.2702          |
+| 2.1389        | 0.16  | 70   | 2.2457          |
+| 2.1482        | 0.17  | 75   | 2.2176          |
+| 2.1567        | 0.18  | 80   | 2.1887          |
+| 2.1533        | 0.2   | 85   | 2.1616          |
+| 2.0629        | 0.21  | 90   | 2.1318          |
+| 2.1068        | 0.22  | 95   | 2.0995          |
+| 2.0196        | 0.23  | 100  | 2.0740          |
+| 2.062         | 0.24  | 105  | 2.0461          |
+| 1.9436        | 0.25  | 110  | 2.0203          |
+| 1.9348        | 0.26  | 115  | 1.9975          |
+| 1.8803        | 0.28  | 120  | 1.9747          |
+| 1.9108        | 0.29  | 125  | 1.9607          |
+| 1.7826        | 0.3   | 130  | 1.9506          |
+| 1.906         | 0.31  | 135  | 1.9374          |
+| 1.8745        | 0.32  | 140  | 1.9300          |
+| 1.8634        | 0.33  | 145  | 1.9232          |
+| 1.8561        | 0.35  | 150  | 1.9183          |
+| 1.8371        | 0.36  | 155  | 1.9147          |
+| 1.8006        | 0.37  | 160  | 1.9106          |
+| 1.8941        | 0.38  | 165  | 1.9069          |
+| 1.8456        | 0.39  | 170  | 1.9048          |
+| 1.8525        | 0.4   | 175  | 1.9014          |
+| 1.8475        | 0.41  | 180  | 1.8998          |
+| 1.8255        | 0.43  | 185  | 1.8962          |
+| 1.9358        | 0.44  | 190  | 1.8948          |
+| 1.758         | 0.45  | 195  | 1.8935          |
+| 1.7859        | 0.46  | 200  | 1.8910          |
+| 1.8412        | 0.47  | 205  | 1.8893          |
+| 1.835         | 0.48  | 210  | 1.8875          |
+| 1.8739        | 0.49  | 215  | 1.8860          |
+| 1.9397        | 0.51  | 220  | 1.8843          |
+| 1.8187        | 0.52  | 225  | 1.8816          |
+| 1.8174        | 0.53  | 230  | 1.8807          |
+| 1.8           | 0.54  | 235  | 1.8794          |
+| 1.7736        | 0.55  | 240  | 1.8772          |
+| 1.7429        | 0.56  | 245  | 1.8778          |
+| 1.8024        | 0.58  | 250  | 1.8742          |
+| 1.8431        | 0.59  | 255  | 1.8731          |
+| 1.7692        | 0.6   | 260  | 1.8706          |
+| 1.8084        | 0.61  | 265  | 1.8698          |
+| 1.7602        | 0.62  | 270  | 1.8705          |
+| 1.7751        | 0.63  | 275  | 1.8681          |
+| 1.7403        | 0.64  | 280  | 1.8672          |
+| 1.8078        | 0.66  | 285  | 1.8648          |
+| 1.8464        | 0.67  | 290  | 1.8648          |
+| 1.7853        | 0.68  | 295  | 1.8651          |
+| 1.8546        | 0.69  | 300  | 1.8643          |
+| 1.8319        | 0.7   | 305  | 1.8633          |
+| 1.7908        | 0.71  | 310  | 1.8614          |
+| 1.738         | 0.72  | 315  | 1.8625          |
+| 1.8868        | 0.74  | 320  | 1.8630          |
+| 1.7744        | 0.75  | 325  | 1.8621          |
+| 1.8292        | 0.76  | 330  | 1.8609          |
+| 1.7905        | 0.77  | 335  | 1.8623          |
+| 1.7652        | 0.78  | 340  | 1.8610          |
+| 1.8371        | 0.79  | 345  | 1.8611          |
+| 1.7024        | 0.81  | 350  | 1.8593          |
+| 1.7328        | 0.82  | 355  | 1.8593          |
+| 1.7376        | 0.83  | 360  | 1.8606          |
+| 1.747         | 0.84  | 365  | 1.8601          |
+| 1.7777        | 0.85  | 370  | 1.8602          |
+| 1.8701        | 0.86  | 375  | 1.8598          |
+| 1.7165        | 0.87  | 380  | 1.8579          |
+| 1.779         | 0.89  | 385  | 1.8588          |
+| 1.8536        | 0.9   | 390  | 1.8583          |
+| 1.7263        | 0.91  | 395  | 1.8582          |
+| 1.7983        | 0.92  | 400  | 1.8587          |
+### Framework versions
+- PEFT 0.7.1
+- Transformers 4.37.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1
+# Citation
 <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 **BibTeX:**
+```
+@misc{ShieldX/manovyadh-1.1B-v1,
+      url={[https://huggingface.co/ShieldX/manovyadh-1.1B-v1](https://huggingface.co/ShieldX/manovyadh-1.1B-v1)},
+      title={ManoVyadh},
+      author={Rohan Shaw},
+      year={2024}, month={Jan}
+}
+```
+# Model Card Authors
+ShieldX a.k.a Rohan Shaw
+# Model Card Contact
+email : [email protected]