Spaces:
Sleeping
Sleeping
train
Browse files- app.ipynb +6 -5
- train.ipynb +64 -21
app.ipynb
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"cell_type": "code",
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"execution_count": 5,
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"id": "6e0bf9da",
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"metadata": {
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"cell_type": "code",
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"execution_count": 16,
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"id": "82774c08",
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"metadata": {
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"data": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.
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"toc": {
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"base_numbering": 1,
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"cell_type": "code",
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"execution_count": 5,
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"id": "6e0bf9da",
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"metadata": {},
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"outputs": [
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"data": {
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"cell_type": "code",
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"execution_count": 16,
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"id": "82774c08",
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"metadata": {
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"scrolled": true,
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"tags": []
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"outputs": [
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"data": {
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"name": "python",
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"version": "3.7.11"
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"toc": {
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"base_numbering": 1,
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train.ipynb
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"outputs": [],
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"learn.fine_tune(3)"
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" <tbody>\n",
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"outputs": [],
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"learn.fine_tune(3)"
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"metadata": {},
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"source": [
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"We could try a better model, based on [this analysis](https://www.kaggle.com/code/jhoward/which-image-models-are-best/). The convnext models work great!"
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]
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},
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"id": "6ee4197a-25be-48ac-a167-903bec5186b1",
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['convnext_base',\n",
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" 'convnext_base_384_in22ft1k',\n",
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" 'convnext_base_in22ft1k',\n",
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" 'convnext_base_in22k',\n",
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" 'convnext_large',\n",
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" 'convnext_large_384_in22ft1k',\n",
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" 'convnext_large_in22ft1k',\n",
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" 'convnext_large_in22k',\n",
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" 'convnext_nano_hnf',\n",
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" 'convnext_small',\n",
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" 'convnext_small_384_in22ft1k',\n",
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" 'convnext_small_in22ft1k',\n",
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" 'convnext_small_in22k',\n",
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" 'convnext_tiny',\n",
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" 'convnext_tiny_384_in22ft1k',\n",
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" 'convnext_tiny_hnf',\n",
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" 'convnext_tiny_hnfd',\n",
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" 'convnext_tiny_in22ft1k',\n",
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" 'convnext_tiny_in22k',\n",
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" 'convnext_xlarge_384_in22ft1k',\n",
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" 'convnext_xlarge_in22ft1k',\n",
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" 'convnext_xlarge_in22k']"
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]
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},
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"output_type": "execute_result"
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}
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],
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"source": [
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"timm.list_models('convnext*')"
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]
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},
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{
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"cell_type": "code",
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"id": "67d34f88-a580-48b9-9b42-e9d0c7e3e870",
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" <td>1.113290</td>\n",
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" <td>0.087957</td>\n",
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